feat(stark): add LogUp lookup argument module with bus abstraction#1159
feat(stark): add LogUp lookup argument module with bus abstraction#1159diegokingston wants to merge 14 commits intomainfrom
Conversation
Add a reusable LogUp lookup argument as a first-class module in the STARK prover. Users declare bus interactions declaratively and get automatic auxiliary trace columns, constraints, and boundary conditions. - Add core types: BusInteraction, BusValue, Multiplicity, LinearTerm - Add degree-2 LookupTermConstraint and degree-1 LookupAccumulatedConstraint - Add AirWithLogUp struct implementing AIR with automatic LogUp wiring - Add trace builder helpers for term and accumulated columns - Add AsBytes, ByteConversion, HasDefaultTranscript for Goldilocks fields - Add TraceTable::allocate_aux_table() for dynamic aux column allocation
Kimi AI ReviewHere are my feedback and observations on the provided PR diff:
Overall, the changes appear to be well-structured and correctly implemented. However, it's important to thoroughly test the new functionality to ensure that it works as expected and does not introduce any regressions. Additionally, the introduction of new features and types should be accompanied by clear documentation to help users understand how to use the new functionality. |
![github-actions[bot]](https://avatars.githubusercontent.com/in/15368?s=60&v=4){kind=small}
|
|
||
| // ===================================================== | ||
| // TESTS | ||
| // ===================================================== |
There was a problem hiding this comment.
Correctness
- Check that the changes involving
ByteConversionforFieldElement<Degree2GoldilocksExtensionField>handle edge cases correctly. Particularly, ensure the new implementation correctly handles the case where the input byte slice is exactly 16 bytes long.
Security
- In the
get_random_field_element_from_rngfunction, ensure that the sample byte array is securely zeroized after use to avoid any leakage of sensitive data. - Consider the possibility of timing side-channels in the
if int_sample < GOLDILOCKS_PRIMEcheck due to branching based on secret data (the prime check).
Performance
- Ensure that the use of
alloc::vec::Vec::<u8>::with_capacity(16)is efficient and necessary. Consider alternatives if allocations can be reduced.
Bugs & Errors
- Use of unchecked
unwraporpaniccould cause potential runtime issues; verify that this is expected behavior and double-check that all error cases are properly handled (e.g., unexpected byte lengths).
Code Simplicity
- The implementation of
from_bytes_beandfrom_bytes_leis quite similar; consider refactoring to avoid code duplication and improve maintainability.
Overall, this pull request addresses the implementation of byte conversion traits and transcript support for cryptographic field elements. Correct attention is needed for edge case handling, potential security vulnerabilities, such as timing attacks and proper zeroization of sensitive data, and ensuring efficient memory usage. Address these concerns before merging.
| pub mod lookup; | ||
| pub mod multi_table_prover; | ||
| pub mod multi_table_verifier; | ||
| pub mod proof; |
There was a problem hiding this comment.
The code introduces a new module lookup, but no specific code was provided for review in the context given. Please ensure to review the following aspects of the new module:
- Correctness: Ensure that operations such as lookup tables (if applicable) correctly handle all edge cases, including out-of-bound indices and zero elements.
- Security: Verify that any use of secret data is constant-time and does not introduce side-channel vulnerabilities. Additionally, confirm that any randomness required is cryptographically secure and properly zeroizes sensitive data.
- Performance: Check for unnecessary allocations and ensure efficient lookups, possibly amortizing costs of repeated operations.
- Bugs & Errors: Make sure there are no panics with index operations and no potential for buffer overflows or memory safety issues.
Without the actual implementation code for the lookup module, it's challenging to assess these critical aspects fully. Please provide the code changes to conduct a thorough review.
| &mut DefaultTranscript::<E>::new(&[]), | ||
| )); | ||
| } | ||
| } |
There was a problem hiding this comment.
Correctness
- Mathematical Operations: The code seems to correctly implement mathematical operations for the AIR (Algebraic Intermediate Representation) with LogUp lookup argument support. Field operations and constraint setups appear correct but require further validation on their mathematical soundness which can be comprehensive.
- Edge Cases: There is no explicit handling for edge cases like zero values or potential identity elements in auxiliary columns, which might lead to potential overflow or invalid constraints.
- Proof System Correctness: The proof system setup seems to follow standard transitions and boundary constraint establishment; however, testing dynamism and edge handling needs to be ensured.
Security
- Timing Side-Channels: Throughout the implementation, there isn't explicit handling to ensure constant-time algorithms. Consider verifying operations on sensitive data to prevent timing variations.
- Zeroization of Sensitive Data: The use of
Mutexand lack of explicit zeroization could lead to potential memory residues of sensitive data. - Cryptographically Secure Randomness: The use of randomness in challenge generation from transcripts should be ensured for secure cryptographic practices; further validation is suggested.
- Secret-dependent Branching: There is inherent complexity in dynamic constraint establishment which might involve hidden branching affecting timings. Ensure consistent conditional execution paths.
- Hash Function Domain Separation: Ensure that hash functions utilized in the transcript avoid reuse across unrelated contexts, though not evident here.
Performance
- MSM and FFT Efficiency: There is no explicit mention of optimizations around FFT pre-computation or efficiency handling for MSM (Multi-Scalar Multiplication) which can improve performance.
- Unnecessary Allocations: Using
Mutexfor storing public inputs might lead to performance hitches; suggest using single-threaded safe storage unless necessary.
Bugs & Errors
- Potential Panics/Unwraps: The code makes use of
expectwhich could lead to panics; consider using non-panicking error handling techniques. - Memory Safety Issues: There are no direct evidences of memory safety issues, but usage of shared data structures with concurrent access should be reviewed.
- Off-by-One Errors: Ensure correctness in cumulative index calculations for the accumulated column and boundary constraints which might lead to off-by-one logic errors.
Code Simplicity
- Overly Complex Implementations: The code tries to encapsulate constraints setup dynamically which can lead to maintenance challenges without clear abstractions.
Attention to correct error handling, security hygiene, and optimizations is advised before this can be considered good to merge.
| result | ||
| } | ||
| } | ||
| } |
There was a problem hiding this comment.
Correctness
- Fingerprint Calculation: The implementation subtracts the sum directly in the
fingerprintcalculation. It's crucial that the mathematical operations adhere to the correct field arithmetic, ensuring that the operations remain within the field constraints. Consider verifying ifz - bus_elements.sum()is computed within the field itself. - Edge Cases: Ensure that zero and identity elements are appropriately treated. For instance, the subtraction operation in
fingerprintshould be scrutinized for zero or identity operations.
Security
- Timing Side-channels: There is a possible timing side-channel in
compute_multiplicitydue to the conditional operation for determining thecoeff. Consider using constant-time operations for these calculations. - Zeroization: No explicit zeroization of sensitive data before deallocating memory is evident. This should be addressed to prevent potential leakage of sensitive information.
Performance
- Redundant Field Inversions: There don't seem to be redundant inversions in the given code section.
- Efficiency: The bus elements array
bus_elementsis created and filled by extending, which might not be optimal in terms of performance. Suggest using iterators or initializing with the exact size.
Bugs & Errors
- Panics or Unwraps: The code safely handles evaluations without any direct panics or unwraps.
- Integer Overflow/Underflow: Consider using Rust's checked arithmetic operations for defining the
coeffto prevent potential overflow/underflow.
Code Simplicity
- Complexity: The computation in
Linearterm ofcompute_multiplicityappears somewhat complex. Refactoring might help readability. - Duplicated Code: The match arms in
evaluatefor Prover and Verifier are almost identical, consider refactoring to reduce duplication.
Overall, the mathematical operations and functions need to ensure they're adhering to field properties and secure against side-channel attacks. Without these improvements, the changes are not ready to merge.
| pub mod types; | ||
|
|
||
| pub use air::AirWithLogUp; | ||
| pub use types::*; |
There was a problem hiding this comment.
The code snippet provided offers minimal context, but here's a general analysis:
-
Security:
- Ensure that any operations on secret data are performed in constant time to avoid timing side-channels.
- Check that sensitive data is properly zeroized after use, especially in cryptographic contexts.
- Verify that cryptographically secure random functions (like
rand::rngs::OsRnginstead ofrand::thread_rng) are used for generating keys or nonces. - Ensure no secret-dependent branching is occurring that could lead to timing side-channel vulnerabilities.
-
Correctness:
- In cryptographic implementations, verify that modular arithmetic operations correctly wrap around a prime modulus and handle edge cases like zero, identity elements, and potential infinity points safely.
- If polynomial operations or FFT are present, confirm they are handling edge cases and the implementations match the expected mathematical properties.
- Any proof system functions need to be validated for mathematical correctness and logical soundness.
-
Performance:
- Review the code for unnecessary memory allocations which can be optimized for better performance.
- Look for redundant inverse calculations that could be optimized using pre-computed values.
- Ensure MSM (Multi-Scalar Multiplication) and FFT (Fast Fourier Transform) operations are optimized for efficiency.
-
Bugs & Errors:
- Watch for potential panics from
unwrap()or indexing operations, especially if the inputs are not guaranteed to be within bounds. - Check for possible memory safety issues, like accessing uninitialized memory or improper use of unsafe blocks (if present).
- Validate against off-by-one errors that can commonly occur in loops or array operations.
- Ensure that integer operations aren't causing overflow or underflow problems, and if applicable, handle them using checked operations.
- Watch for potential panics from
-
Code Simplicity:
- Avoid overly complex implementations which could be simplified for better readability and maintainability.
- Refactor any duplicated code into functions or modules to adhere to the DRY principle.
- Ensure abstractions are appropriately used to encapsulate complexity and provide clear interfaces.
Since the snippet does not expose specific code implementations, please ensure a thorough review of the actual module files for the points mentioned above before proceeding to merge.
| result | ||
| } | ||
| } | ||
| } |
There was a problem hiding this comment.
Correctness
- Handling of zero: While the comment indicates that sampling zero for
fingerprintis negligible, it should be explicitly handled to avoid any unexpected panics during the division operation. Consider safe handling instead of depending solely on probability. - Infinity points: There should be clear checks if any operation could result in an 'infinity' or undefined point or term, especially in elliptic curve calculations (though not directly visible here, it's a good practice to advise ensuring elsewhere).
Security
- Possible Timing Side-Channel: The
fingerprint.inv()operation could potentially introduce timing side-channels. Ensure that all operations involving secret keys or data are constant time. - Zeroization: There are no explicit operations for zeroizing sensitive data, particularly
accumulatedorrow_sumwhich could contain sensitive results.
Performance
- Unnecessary Allocations: The
Vec<FieldElement<E>>foralpha_powersis created without initializing with a fixed size or using an efficient iterator; while this isn't critical, it might harm performance under certain conditions.
Bugs & Errors
- Panics: The use of
.expect()onfingerprint.inv()can cause a panic if the operation is invalid, even if intended probabilities are negligible. Always code defensively. - Potential overflow/underflow: Ensure
FieldElementimplementations handle these cases correctly in the context of cryptographic operations.
Code Simplicity
- While the implementation of multiplicity and linearity with nested matches looks compact, it could potentially be refactored for simplicity ensuring the logic paths are clear for future maintainers.
Recommendation
- Address the security concerns, especially around potential panics and side-channels. Implement a secure error handling for cases that can trigger panics, and ensure operations remain constant time where it counts. Overall, while the core logic seems mathematically sound, careful handling of edge cases and security factors need to be improved before considering merging.
| F: IsFFTField + IsSubFieldOf<E> + Send + Sync, | ||
| E: IsField + Send + Sync, | ||
| { | ||
| } |
There was a problem hiding this comment.
Correctness:
- Polynomial and Field Operations: The
combine_frommethod correctly iterates overLinearTermand handles operations, whether it involves positive or negative coefficients. However, you should ensureFieldElementsupports operations on potentially largeu64converted fromi64without overflow issues in the field's order capacity. - Edge Cases: Check the handling of zero for coefficients and constants. Ensure any zero behavior aligns with expectations in field operations.
Security:
- Timing Side-channels: Ensure that operations on
FieldElementare constant-time, especially when handling cryptographic secrets. Even though this is not immediately visible withinBusValue/BusInteraction, underlying operations should maintain constant-time properties. - Zeroization: Sensitive data (if any) needs proper zeroization after use to prevent leakages.
Performance:
- Redundant Computations: Repeated conversions in
combine_fromfor handlingi64coefficients every time a condition is checked could potentially be optimized by caching the result based on the sign once.
Bugs & Errors:
- Panics or Unwraps: No direct use of
unwrapin reviewed code. Ensure error conditions are handled gracefully in other potentially related modules. - Overflow/Underflow: Conversion from
i64tou64viaas u64under negative values in combination operations should be carefully scrutinized for overflow risk in the respective finite fields.
Code Simplicity:
-
Complexity and Abstractions: The current setup divides concerns clearly with distinct roles for
BusInteraction,BusValue, andLinearTerm, supporting a clean architectural partition beneficial for future maintenance and extension. -
Duplicated Logic: No obvious duplication except consideration for the optimization of coefficient handling as mentioned.
Conclusively, before merging, it is crucial to address the concerns around field operations on possibly large coefficients and ensuring security with constant-time reinforcement. Addressing these will ensure robustness against edge cases and security vulnerabilities.
|
|
||
| pub fn allocate_with_zeros( | ||
| num_steps: usize, | ||
| num_main_columns: usize, |
There was a problem hiding this comment.
Correctness
- The
allocate_aux_tablefunction initializes the auxiliary table with zeros. Ensure that this zero initialization suits the application context, especially regarding polynomial operations or elliptic curve computations where zeros might have specific implications.
Security
- Ensure that zero-initialization does not pose any security risk. If these fields contain secret-dependent data, they must be securely overwritten.
Performance
- Using a
vec!to initialize elements might be inefficient if the number of allocations is large. Consider using a more efficient allocation strategy, if applicable.
Bugs & Errors
- There might be a panic if
num_aux_columnsorself.num_rows()returns very large numbers due to excessive allocation size. Consider handling this with appropriate checks and early return or error reporting.
Code Simplicity
- Code appears simple and within the established patterns. Ensure that the
allocate_aux_tablemethod is consistent with other table management methods and does not duplicate logic elsewhere.
Codecov Report❌ Patch coverage is Additional details and impacted files@@ Coverage Diff @@
## main #1159 +/- ##
==========================================
+ Coverage 73.48% 73.56% +0.08%
==========================================
Files 182 186 +4
Lines 41364 42038 +674
==========================================
+ Hits 30396 30926 +530
- Misses 10968 11112 +144 ☔ View full report in Codecov by Sentry. 🚀 New features to boost your workflow:
|
Greptile OverviewGreptile SummaryThis PR introduces a first-class LogUp lookup module in the STARK prover. It adds a On the math side, it extends Goldilocks field types with Confidence Score: 2/5
|
| Filename | Overview |
|---|---|
| crates/math/src/field/fields/u64_goldilocks_field.rs | Adds AsBytes/ByteConversion for Goldilocks quadratic extension and implements HasDefaultTranscript for Goldilocks base and degree-2 extension. |
| crates/provers/stark/src/lib.rs | Exports new lookup module from the STARK crate. |
| crates/provers/stark/src/lookup/air.rs | Introduces AirWithLogUp wrapper that auto-builds LogUp aux columns/constraints; current boundary constraints are derived from the witness (tautological) and aux allocation can overwrite existing aux data. |
| crates/provers/stark/src/lookup/constraints.rs | Adds term (deg-2) and accumulated (deg-1) transition constraints for LogUp term columns and running sum. |
| crates/provers/stark/src/lookup/mod.rs | Adds lookup module wiring and re-exports AirWithLogUp and lookup types. |
| crates/provers/stark/src/lookup/trace_builder.rs | Adds helpers to build LogUp term columns (sign*multiplicity/fingerprint) and accumulated running-sum column. |
| crates/provers/stark/src/lookup/types.rs | Adds LogUp bus abstraction types (BusInteraction/BusValue/Multiplicity/LinearTerm) and boundary-constraint builder trait. |
| crates/provers/stark/src/trace.rs | Adds TraceTable::allocate_aux_table() to dynamically allocate zeroed aux columns. |
Sequence Diagram
sequenceDiagram
participant User as User AIR (custom)
participant Air as AirWithLogUp
participant Trace as TraceTable
participant Prover as Prover
participant Transcript as Transcript
participant Verifier as Verifier
User->>Air: AirWithLogUp::new(interactions, user_constraints)
Prover->>Transcript: sample RAP challenges
Transcript-->>Prover: [z, alpha]
Prover->>Air: build_auxiliary_trace(trace, [z, alpha])
Air->>Trace: allocate_aux_table(N+1) if needed
loop each interaction i
Air->>Trace: build_logup_term_column(i)
end
Air->>Trace: build_accumulated_column(N)
Air->>Air: store BusPublicInputs (from trace)
Prover->>Air: boundary_constraints([z, alpha])
Air-->>Prover: boundary + user boundary constraints
Prover->>Prover: commit trace, evaluate transition constraints
Verifier->>Air: boundary_constraints([z, alpha])
Air-->>Verifier: same boundary constraints
Verifier->>Verifier: verify commitments + constraints
![greptile-apps[bot]](https://avatars.githubusercontent.com/in/867647?s=60&v=4){kind=small}
| // Store public inputs for boundary constraints | ||
| let last_row = trace.num_rows() - 1; | ||
| let bus_pi = BusPublicInputs { | ||
| initial_value: trace.get_aux(0, acc_col_idx).clone(), | ||
| final_accumulated: trace.get_aux(last_row, acc_col_idx).clone(), | ||
| }; |
There was a problem hiding this comment.
Boundary constraints become tautologies
build_auxiliary_trace stores initial_value and final_accumulated by reading them back from the trace (get_aux(...)) and then boundary_constraints enforces the accumulated column equals those same values at row 0 / last row. Since both values are derived from the witness, these boundary constraints don’t constrain the witness at all (they’re always satisfiable for any accumulated column values). If LogUp needs the final accumulated value to equal a public value (typically 0 for a balanced bus), it should come from pub_inputs (or some explicit public input) rather than being copied from the trace.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/air.rs
Line: 182:187
Comment:
**Boundary constraints become tautologies**
`build_auxiliary_trace` stores `initial_value` and `final_accumulated` by *reading them back from the trace* (`get_aux(...)`) and then `boundary_constraints` enforces the accumulated column equals those same values at row 0 / last row. Since both values are derived from the witness, these boundary constraints don’t constrain the witness at all (they’re always satisfiable for any accumulated column values). If LogUp needs the final accumulated value to equal a public value (typically 0 for a balanced bus), it should come from `pub_inputs` (or some explicit public input) rather than being copied from the trace.
How can I resolve this? If you propose a fix, please make it concise.| // Allocate aux table if needed | ||
| let (_, num_aux_columns) = self.trace_layout; | ||
| if num_aux_columns > 0 && trace.num_aux_columns == 0 { | ||
| trace.allocate_aux_table(num_aux_columns); | ||
| } |
There was a problem hiding this comment.
Aux allocation can wipe data
build_auxiliary_trace calls trace.allocate_aux_table(num_aux_columns) whenever trace.num_aux_columns == 0. If the caller constructed a TraceTable that already has an aux_table (e.g., via TraceTable::from_columns), but forgot to set num_aux_columns consistently (or it’s 0 for other reasons), this will overwrite the existing aux data with zeros. Since TraceTable’s fields are public, this state is representable and would silently corrupt the witness.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/air.rs
Line: 167:171
Comment:
**Aux allocation can wipe data**
`build_auxiliary_trace` calls `trace.allocate_aux_table(num_aux_columns)` whenever `trace.num_aux_columns == 0`. If the caller constructed a `TraceTable` that already has an `aux_table` (e.g., via `TraceTable::from_columns`), but forgot to set `num_aux_columns` consistently (or it’s 0 for other reasons), this will overwrite the existing aux data with zeros. Since `TraceTable`’s fields are public, this state is representable and would silently corrupt the witness.
How can I resolve this? If you propose a fix, please make it concise.…in LogUp - Change accumulated constraint end_exemptions from 1 to 0 so the transition wraps around, pinning acc[0] = acc[N-1] + Σ terms[0] - Hardcode acc[N-1] = 0 boundary constraint for bus balance instead of reading witness values (which made constraints tautological) - Remove Mutex<BusPublicInputs> pattern, no longer needed - Fix aux allocation check to handle mismatched column counts
Kimi AI ReviewThis PR introduces several changes to the File:
|
|
|
||
| let num_aux_columns = if num_interactions > 0 { | ||
| num_interactions + 1 | ||
| } else { |
There was a problem hiding this comment.
Correctness
- The removal of storing and checking
initial_valueandfinal_accumulatedfor the boundary constraints in thebus_public_inputsseems to change the intended behavior for boundary constraints. Without comparing these values, boundary conditions may not be properly enforced for the STARK.
Security
- No new security issues identified. The use of a
Mutexitself didn't introduce a security risk but ensure its removal doesn't affect concurrent access incorrectly.
Performance
- Allocation of the aux table seems optimized now, only being triggered when dimensions don't match.
Bugs & Errors
- Possible panic could arise from using unwrapped data due to the extraction of
bus_public_inputs. Ensure no areas of the codebase rely on this state and aren't yet updated. - Mutex removal might introduce race conditions if the public inputs were accessed concurrently elsewhere in the code. Thoroughly test concurrent scenarios if applicable.
Code Simplicity
- Simplification achieved by removing mutex protection on
bus_public_inputs. Further changes seem to indicate a more streamlined constraint checking process.
Summary
- The removal of the
bus_public_inputsand related logic affects correctness by eliminating necessary boundary checks. If transitions rely on these constraints, the logic should either be restored or re-evaluated to ensure correctness. Before merging, ensure to verify refined intention of boundary checks is retained through comprehensive tests.
|
|
||
| use crate::{ | ||
| constraints::transition::TransitionConstraint, table::TableView, | ||
| traits::TransitionEvaluationContext, |
There was a problem hiding this comment.
Review of Code Changes
Correctness:
- Boundary Change in Function
end_exemptions:- The change from returning
1to0in theend_exemptionsfunction could have significant implications on how exemptions are handled. It is important to verify that this change correctly reflects the intended application logic, especially if this function is part of a larger cryptographic or mathematical operation.
- The change from returning
Security:
- No assessment provided in the diff for potential security vulnerabilities like timing side-channels or proper zeroization because the context of the code change doesn't provide enough information about sensitive data handling. Ensure functions dealing with sensitive data (if any) are appropriately constant-time and zeroized after use.
Performance:
- Potential Impact on Logic Execution:
- Altering the return value from
1to0might affect loops or logical checks where exemptions are iterated over. Review associated code for performance constraints if this change results in larger loops or operations.
- Altering the return value from
Bugs & Errors:
- Implications of Returning
0:- If a function, array access, or index relies on this return value, returning
0could introduce potential panics (if this is used as a divisor or index) or off-by-one errors. Evaluate this thoroughly against the entire code logic that uses this function.
- If a function, array access, or index relies on this return value, returning
Code Simplicity:
- No Information on Complexity:
- Without additional context, it is unclear if this change results in duplications or unnecessary complexity; however, it appears to be a simple single-line change.
Overall, the change requires careful consideration of its impact on the logic surrounding exemptions. More context is needed to ensure this modification is intentional and correct. Please verify any associated logic affected by this change before approving the integration.
…onstraints - Change AIR::build_auxiliary_trace to return Result<(), ProvingError> so trace-building errors propagate to the prover instead of panicking - Return ProvingError::WrongParameter on zero fingerprint in LogUp trace builder (astronomically unlikely but must be handled) - Document that multiplicity columns must be constrained by the user's main AIR — the LogUp module uses them but does not verify them - Update all existing build_auxiliary_trace implementations
Keep build_auxiliary_trace error propagation with ? and adopt main's Result-based interpolate_and_commit_aux.
Kimi AI ReviewHere are my feedback and issues found in the PR diff:
These are the main issues found in the PR diff. Please address these issues to ensure the code is correct and compilable. |
The AsBytes trait is defined with #[cfg(feature = "alloc")], so its import must also be conditional to compile without the alloc feature.
| @@ -299,6 +302,13 @@ | |||
There was a problem hiding this comment.
Correctness:
- Ensure appropriate mathematical checks for edge cases such as zero, identity elements, and infinity points in elliptic curve operations are in place. This section of the diff does not provide enough context to confirm these checks.
Security:
- Feature-Gated Allocations: Make sure that the feature-gated
AsBytestrait usage does not create scenarios where allocation-related features are enabled without strict necessity, potentially affecting memory safety or security. Check ifallocfeature is handled securely where randomness and cryptographic operations are concerned. - The code does not provide enough information to verify constant-time operations and secure zeroization. Ensure secret-dependent operations do not inadvertently leak information.
Bugs & Errors:
- Since this code introduces conditional compilation, be cautious with feature gates creating inconsistent builds which might introduce off-by-one errors or memory safety issues inadvertently.
Code Simplicity:
- The changes show no indication of overly complex implementations, but verify that related code sections maintain a balance between abstraction and simplicity.
The modification currently does not provide sufficient context on correctness and security measures; further examination of related code sections is required to make a conclusive assessment.
Kimi AI ReviewHere are my feedback and issues found in the PR diff:
These are the main issues I found in the PR diff. Please address these points to improve the code quality and robustness. |
Kimi AI ReviewHere are my feedback and issues found in the PR diff:
These are the main issues I found in the PR diff. Addressing these points will improve the code quality, maintainability, and reliability of the new features. |
|
@greptile |
Greptile OverviewGreptile SummaryThis PR adds a first-class LogUp lookup argument module to the STARK prover. It introduces Key integration point: Confidence Score: 4/5
|
| Filename | Overview |
|---|---|
| crates/math/src/field/fields/u64_goldilocks_field.rs | Adds AsBytes/ByteConversion for Goldilocks and degree-2 extension plus HasDefaultTranscript impls; feature-gating for alloc looks consistent. |
| crates/provers/stark/src/examples/fibonacci_rap.rs | Updates build_auxiliary_trace to return Result<(), ProvingError> and adds Ok(()). |
| crates/provers/stark/src/examples/read_only_memory.rs | Updates build_auxiliary_trace to return Result<(), ProvingError> and adds Ok(()). |
| crates/provers/stark/src/examples/read_only_memory_logup.rs | Updates build_auxiliary_trace signature to return Result for new AIR trait; no functional change beyond returning Ok(()). |
| crates/provers/stark/src/lib.rs | Exports new lookup module. |
| crates/provers/stark/src/lookup/air.rs | Introduces AirWithLogUp wrapper implementing AIR, auto-builds term/acc constraints and aux trace; contains aux-table reallocation that can overwrite pre-filled aux witness data when metadata mismatches. |
| crates/provers/stark/src/lookup/constraints.rs | Adds LogUp term (deg-2) and accumulated (deg-1) transition constraints plus multiplicity evaluation helper. |
| crates/provers/stark/src/lookup/trace_builder.rs | Adds helper functions to build term columns and accumulated column for LogUp aux trace; returns error on zero fingerprint. |
| crates/provers/stark/src/lookup/types.rs | Adds core LogUp types (BusInteraction, BusValue, Multiplicity, LinearTerm) and boundary constraint builder trait. |
| crates/provers/stark/src/prover.rs | Propagates errors from build_auxiliary_trace via ? in round 1. |
| crates/provers/stark/src/trace.rs | Adds TraceTable::allocate_aux_table() to allocate zeroed aux columns; correct but can be used in ways that overwrite existing aux data if called after aux witness was populated. |
| crates/provers/stark/src/traits.rs | Changes AIR::build_auxiliary_trace to return Result<(), ProvingError> and imports ProvingError. |
Sequence Diagram
sequenceDiagram
participant Prover
participant AIR as AirWithLogUp (AIR)
participant Trace as TraceTable
participant TB as LogUp trace_builder
participant LDE as LDETraceTable
participant Eval as Evaluator/Frame
participant Verifier
Prover->>AIR: build_rap_challenges(transcript)
AIR-->>Prover: [z, alpha]
alt AIR.has_trace_interaction()
Prover->>AIR: build_auxiliary_trace(trace, challenges)
AIR->>Trace: allocate_aux_table(num_interactions+1)
loop each interaction i
AIR->>TB: build_logup_term_column(i, interaction, trace, challenges)
TB->>Trace: set_aux(row, i, term[row])
end
AIR->>TB: build_accumulated_column(acc_idx, num_terms, trace)
TB->>Trace: set_aux(row, acc_idx, accumulated[row])
end
Prover->>LDE: from_columns(main_evals, aux_evals, step_size, blowup)
Prover->>Eval: compute boundary polys/transition evals
Eval->>LDE: get_main/get_aux rows
Eval->>AIR: transition_constraints().evaluate(...)
Prover-->>Verifier: proof (commitments, challenges, openings)
Verifier->>AIR: boundary_constraints(rap_challenges)
Verifier->>Eval: recompute evaluations, check constraints
Verifier-->>Prover: accept/reject
| if num_aux_columns > 0 && trace.num_aux_columns != num_aux_columns { | ||
| trace.allocate_aux_table(num_aux_columns); | ||
| } |
There was a problem hiding this comment.
Aux trace allocation drops witness
build_auxiliary_trace reallocates the entire aux table whenever trace.num_aux_columns != num_aux_columns (lookup/air.rs:167-169). Since TraceTable fields are public, callers can represent a state where aux_table already contains witness data but num_aux_columns is stale; this code will silently overwrite that data with zeros. This is a definite correctness bug when any AIR relies on pre-populated aux columns. Consider validating consistency (e.g., error if aux_table.width != 0 and mismatch) rather than reallocating, or derive the source of truth from aux_table.width.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/air.rs
Line: 167:169
Comment:
**Aux trace allocation drops witness**
`build_auxiliary_trace` reallocates the entire aux table whenever `trace.num_aux_columns != num_aux_columns` (`lookup/air.rs:167-169`). Since `TraceTable` fields are public, callers can represent a state where `aux_table` already contains witness data but `num_aux_columns` is stale; this code will silently overwrite that data with zeros. This is a definite correctness bug when any AIR relies on pre-populated aux columns. Consider validating consistency (e.g., error if `aux_table.width != 0` and mismatch) rather than reallocating, or derive the source of truth from `aux_table.width`.
How can I resolve this? If you propose a fix, please make it concise.
| /// | ||
| /// This is degree 2 because it multiplies the aux column (`term`) by | ||
| /// the fingerprint (which is linear in main trace values). | ||
| pub(crate) struct LookupTermConstraint { |
There was a problem hiding this comment.
Correctness:
- The change from using
alpha.pow(i)to an iterative multiplication for computing powers ofalphaappears correct mathematically, as it should yield the same result while being more efficient. However, ensure that theFieldElementtype handles addition and multiplication correctly, particularly in terms of respecting field properties such as commutativity, associativity, and proper modular reduction.
Security:
- There's no indication of handling constant-time operations. If
alphaorbus_elementscontain secret data, ensure the arithmetic is performed in a constant-time manner to prevent side-channel attacks. - There are no indications of zeroization of sensitive data, such as temporary values used in the fingerprint calculation. Consider zeroizing these values if they contain cryptographic secrets.
Performance:
- Using an iterative approach to calculate
alphapowers is more efficient than usingpowrepeatedly, as it avoids redundant computations. This is a good optimization.
Bugs & Errors:
- Ensure there is no possibility of a panic due to overflow in the index or if the bus_elements contains unexpected values leading to invalid field operations. These concerns seem minimal due to the nature of Rust's safety guarantees, but review any custom implementations in FieldElement.
Code Simplicity:
- The replacement of the pow-based approach with an iterative method simplifies the computation and should be easier to maintain. The iterative logic is clear and avoids the overhead of recalculating each power.
Overall, the change is in the right direction for performance, but the security concerns regarding constant-time operations and zeroization need addressing before merging.
Kimi AI ReviewHere are the issues I found in the PR diff:
These are the main issues I found in the PR diff. Please address these points to ensure the code is robust and maintainable. |
|
@greptile |
Greptile OverviewGreptile SummaryThis PR introduces a first-class LogUp lookup argument module for the STARK prover: core interaction types ( Overall the direction fits the existing AIR/TraceTable architecture by implementing lookup as an auxiliary-trace + constraint bundle, but there are correctness issues in the accumulator transition constraint and a prover/verifier mismatch risk in fingerprint power computation that should be addressed before merge. Confidence Score: 2/5
|
| Filename | Overview |
|---|---|
| crates/math/src/field/fields/u64_goldilocks_field.rs | Adds AsBytes/ByteConversion/HasDefaultTranscript impls for Goldilocks and degree-2 extension; review focuses on byte encoding consistency and transcript defaults. |
| crates/provers/stark/src/examples/fibonacci_rap.rs | Updates STARK example to integrate LogUp lookup wiring; no immediate correctness issues spotted in example usage. |
| crates/provers/stark/src/examples/read_only_memory.rs | Example adjustments to support new trace/traits APIs; changes appear localized to demo code. |
| crates/provers/stark/src/examples/read_only_memory_logup.rs | Introduces/updates LogUp-based read-only memory example; primarily demonstrates new lookup module. |
| crates/provers/stark/src/lib.rs | Wires new lookup module exports into crate; expected re-exports/feature plumbing only. |
| crates/provers/stark/src/lookup/air.rs | Adds AirWithLogUp and auxiliary trace building/boundary handling; previous review threads already flagged boundary tautology and aux allocation overwrites; remaining review focuses on constraint soundness and indexing. |
| crates/provers/stark/src/lookup/constraints.rs | Adds lookup term and accumulated constraints (degree-2/degree-1); review focuses on edge rows and division-by-zero avoidance. |
| crates/provers/stark/src/lookup/mod.rs | New lookup module root; mostly module organization and re-exports. |
| crates/provers/stark/src/lookup/trace_builder.rs | Trace builder helpers for allocating/filling LogUp term/accumulated auxiliary columns; review focuses on correct row iteration and column alignment. |
| crates/provers/stark/src/lookup/types.rs | Adds core LogUp types (BusInteraction, BusValue, Multiplicity, LinearTerm); review focuses on type invariants and evaluation semantics. |
| crates/provers/stark/src/prover.rs | Integrates LogUp aux building into prover flow; review focuses on ordering (aux built before commitments/constraints) and compatibility with existing traces. |
| crates/provers/stark/src/trace.rs | Adds TraceTable::allocate_aux_table for dynamic aux column allocation; review focuses on preserving existing aux data and keeping width fields consistent. |
| crates/provers/stark/src/traits.rs | Adds/extends traits to support LogUp wiring (AIR wrapper, auxiliary trace hooks); review focuses on trait method contracts and default implementations. |
Sequence Diagram
sequenceDiagram
autonumber
participant User as User/AIR author
participant Air as AirWithLogUp
participant TB as TraceTable
participant LTB as LogUpTraceBuilder
participant P as Prover
participant V as Verifier
User->>Air: declare bus interactions (BusInteraction[])
User->>TB: build main trace
P->>Air: build_auxiliary_trace(TB)
Air->>TB: ensure aux width (allocate_aux_table)
Air->>LTB: build term cols + accumulated cols
LTB->>TB: write aux columns (terms, accumulators)
P->>Air: constraints()
Air-->>P: LookupTermConstraint + LookupAccumulatedConstraint
P->>V: commit traces + proofs
V->>Air: constraints()
V->>V: check polynomial constraints + boundary constraints
| fn end_exemptions(&self) -> usize { | ||
| 0 | ||
| } |
There was a problem hiding this comment.
Missing last-row exemption
LookupAccumulatedConstraint reads frame.get_evaluation_step(1) (next row) with end_exemptions() == 0 (lookup/constraints.rs:175-213). On the last row this will use the wrap-around frame, so the constraint becomes acc[0] - acc[last] - Σ terms[0] = 0, which is not the intended running-sum recurrence (and it also changes the meaning of the single boundary constraint in AirWithLogUp). If the accumulator is meant to satisfy acc[i+1] = acc[i] + Σ terms[i+1] only for i < N-1, this constraint needs an end exemption of 1 (or equivalent zerofier logic) so it doesn’t apply on the last step.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/constraints.rs
Line: 175:177
Comment:
**Missing last-row exemption**
`LookupAccumulatedConstraint` reads `frame.get_evaluation_step(1)` (next row) with `end_exemptions() == 0` (`lookup/constraints.rs:175-213`). On the last row this will use the wrap-around frame, so the constraint becomes `acc[0] - acc[last] - Σ terms[0] = 0`, which is *not* the intended running-sum recurrence (and it also changes the meaning of the single boundary constraint in `AirWithLogUp`). If the accumulator is meant to satisfy `acc[i+1] = acc[i] + Σ terms[i+1]` only for `i < N-1`, this constraint needs an end exemption of 1 (or equivalent zerofier logic) so it doesn’t apply on the last step.
How can I resolve this? If you propose a fix, please make it concise.| // Precompute powers of alpha | ||
| let num_bus_elements = interaction.num_bus_elements(); | ||
| let alpha_powers: Vec<FieldElement<E>> = (0..num_bus_elements).map(|i| alpha.pow(i)).collect(); | ||
|
|
There was a problem hiding this comment.
Alpha power mismatch
build_logup_term_column precomputes alpha_powers as (0..num_bus_elements).map(|i| alpha.pow(i)) (lookup/trace_builder.rs:38-41), but the verifier-side constraint computes powers iteratively starting from 1 (lookup/constraints.rs:92-96). These two must match exactly (same starting exponent for the same bus element order) or the prover will fill term columns for a different fingerprint than the one enforced by constraints.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/trace_builder.rs
Line: 38:41
Comment:
**Alpha power mismatch**
`build_logup_term_column` precomputes `alpha_powers` as `(0..num_bus_elements).map(|i| alpha.pow(i))` (`lookup/trace_builder.rs:38-41`), but the verifier-side constraint computes powers iteratively starting from 1 (`lookup/constraints.rs:92-96`). These two must match exactly (same starting exponent for the same bus element order) or the prover will fill term columns for a *different* fingerprint than the one enforced by constraints.
How can I resolve this? If you propose a fix, please make it concise.| let main_segment_cols = trace.columns_main(); | ||
| let trace_len = trace.num_rows(); |
There was a problem hiding this comment.
Quadratic trace cloning
build_logup_term_column calls trace.columns_main() once and then indexes main_segment_cols[col][row] (lookup/trace_builder.rs:32-58). columns_main() builds a fresh Vec<Vec<FieldElement<_>>> by cloning the entire main table (see trace.rs:140-142 → table.rs:91-104), so building each term column incurs a full trace clone. With many interactions this becomes O(#interactions × trace_size) extra copying on top of the actual work. Consider reading directly from trace.main_table (or adding a non-cloning column view API) so LogUp aux building is linear in the trace size.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/trace_builder.rs
Line: 32:33
Comment:
**Quadratic trace cloning**
`build_logup_term_column` calls `trace.columns_main()` once and then indexes `main_segment_cols[col][row]` (`lookup/trace_builder.rs:32-58`). `columns_main()` builds a fresh `Vec<Vec<FieldElement<_>>>` by cloning the entire main table (see `trace.rs:140-142` → `table.rs:91-104`), so building each term column incurs a full trace clone. With many interactions this becomes O(#interactions × trace_size) extra copying on top of the actual work. Consider reading directly from `trace.main_table` (or adding a non-cloning column view API) so LogUp aux building is linear in the trace size.
How can I resolve this? If you propose a fix, please make it concise.
| }; | ||
|
|
||
| use crate::{ | ||
| constraints::{ |
There was a problem hiding this comment.
Issues Found
-
Function Call Update: The call to
build_logup_term_columnwas updated to include&main_segment_cols. Ensure that this additional parameter is intended and thatbuild_logup_term_columnis updated accordingly to handle the new parameter without errors. If this change was accidental, it may lead to runtime issues. -
Potential Performance Issue: Ensure that
trace.columns_main()does not perform unnecessary allocations or data copying. It's important this method returns a reference or efficiently constructed data to avoid redundant computational overhead. -
Safe Handling of Results: Verify that the
?operator's error propagation is handled consistently throughout the code. Ensure there is proper handling of all possible error cases frombuild_logup_term_columnto prevent unwarranted panics. -
Code Simplicity: Consider if the added variable
main_segment_colsis necessary or if the code can be refactored to utilize the existing structure. This can enhance readability and maintainability.
| /// unlikely for randomly sampled challenges, probability ≈ N/|F|). | ||
| pub fn build_logup_term_column<F, E>( | ||
| aux_column_idx: usize, | ||
| interaction: &BusInteraction, |
There was a problem hiding this comment.
-
Correctness: The changes seem to reassign the
main_segment_colsby removing its previous assignment fromtrace.columns_main()and now it's being passed as a parameter. Verify if this aligns with the expected data structure and if its consistency is maintained across the function logic. Also, check if the changes affect the logical flow concerning the computation of trace multiplicity or the use ofbus_elements. -
Performance: Ensure that passing
main_segment_colsas a parameter does not entail unnecessary allocations. The duplication of this data unnecessarily could affect performance. -
Bugs & Errors: Ensure that the
challengesvector access usingLOGUP_CHALLENGE_Zis in bounds to avert potential panics. It should also be guaranteed that the length ofchallengesis adequately validated before indexing. -
Security: Review the safety of
compute_trace_multiplicityandbus_elementsinitializations to assure no secret dependencies lead to time-based side channels. Additionally, verify that sensitive data is appropriately zeroized post usage, especially if engaged in operations involving cryptographic routines. Make sure there's no branch involving secrets that might unveil execution flow. -
Code Simplicity: The direct passing of
main_segment_colsmight enhance simplicity if it circumvents unnecessary transformations or reallocations; however, ensure no changes make the code more complex elsewhere or contradict abstractions.
Confirm all these aspects against relevant tests passing or perhaps new tests if coverage was previously incomplete.
Kimi AI ReviewThis PR introduces several changes, including new features and improvements to the existing codebase. Here are my specific comments and feedback:
|
|
@greptile |
Greptile OverviewGreptile SummaryThis PR adds a new The LogUp module integrates by wrapping a user AIR inside Confidence Score: 3/5
|
| Filename | Overview |
|---|---|
| crates/math/src/field/fields/u64_goldilocks_field.rs | Adds AsBytes/ByteConversion for Goldilocks base + degree-2 extension, plus HasDefaultTranscript sampling for base and degree-2 extension fields. |
| crates/provers/stark/src/examples/fibonacci_rap.rs | Updates AIR::build_auxiliary_trace signature to return Result and propagates Ok(()) in example. |
| crates/provers/stark/src/examples/read_only_memory.rs | Updates AIR::build_auxiliary_trace signature to return Result and returns Ok(()) in example. |
| crates/provers/stark/src/examples/read_only_memory_logup.rs | Updates AIR::build_auxiliary_trace signature to return Result and returns Ok(()) in example. |
| crates/provers/stark/src/lib.rs | Exports new lookup module from stark crate. |
| crates/provers/stark/src/lookup/air.rs | Introduces AirWithLogUp wrapper AIR, builds term/acc aux columns and adds boundary constraint acc[last]=0; prior thread already flags several correctness/perf issues. |
| crates/provers/stark/src/lookup/constraints.rs | Adds term (deg2) and accumulated (deg1) transition constraints for LogUp; prior thread flags missing last-row exemption and alpha power mismatch. |
| crates/provers/stark/src/lookup/trace_builder.rs | Adds aux trace builders for term and accumulated columns; prior thread flags alpha power mismatch and trace cloning performance issue. |
| crates/provers/stark/src/lookup/types.rs | Adds BusInteraction/BusValue/Multiplicity/LinearTerm types; found bug: BusValue::constant truncates u64 to i64 for large constants. |
| crates/provers/stark/src/prover.rs | Propagates errors from AIR::build_auxiliary_trace into prover flow. |
| crates/provers/stark/src/trace.rs | Adds TraceTable::allocate_aux_table helper for dynamic aux allocation; behavior overwrites aux data (already covered in prior thread). |
| crates/provers/stark/src/traits.rs | Changes AIR::build_auxiliary_trace to return Result<(), ProvingError> with default Ok(()) implementation. |
Sequence Diagram
sequenceDiagram
participant User as User/AIR author
participant Air as AirWithLogUp
participant Prover as Prover::prove
participant Transcript as Transcript
participant Trace as TraceTable
participant Aux as LogUp trace_builder
participant Cons as LogUp constraints
User->>Air: new(trace_length, pub_inputs, interactions, ...)
Prover->>Transcript: append(main trace merkle root)
Prover->>Air: build_rap_challenges(transcript)
Air->>Transcript: sample_field_element() z
Air->>Transcript: sample_field_element() alpha
Prover->>Air: build_auxiliary_trace(trace, [z, alpha])
Air->>Trace: allocate_aux_table(if needed)
Air->>Aux: build_logup_term_column(per interaction)
Aux->>Trace: set_aux(term cols)
Air->>Aux: build_accumulated_column
Aux->>Trace: set_aux(acc col)
Prover->>Transcript: append(aux trace merkle root)
Prover->>Cons: evaluate transition constraints over LDE frames
Prover->>Air: boundary_constraints([z, alpha])
Air-->>Prover: includes acc[last]=0 + user boundary constraints
Prover->>Prover: build composition polynomial + FRI
Additional Comments (1)
Consider storing constants as Prompt To Fix With AIThis is a comment left during a code review.
Path: crates/provers/stark/src/lookup/types.rs
Line: 1204:1208
Comment:
**u64 → i64 overflow**
`BusValue::constant` builds `LinearTerm::Constant(value as i64)`. For `value > i64::MAX`, this truncates/wraps and produces a different constant than requested. Since this is a public constructor, callers can hit this with large bus IDs/values.
Consider storing constants as `u64` (or `FieldElement`), or returning an error if the provided `u64` doesn’t fit into `i64`.
How can I resolve this? If you propose a fix, please make it concise. |
Kimi AI ReviewHere are my feedback and comments on the PR diff:
Overall, the PR makes significant improvements to the Stark prover implementation by adding support for the LogUp protocol. The code is well-organized, and the changes are mostly well-implemented. The suggestions above should help further improve the code quality and maintainability. |
| use crate::{ | ||
| constraints::transition::TransitionConstraint, table::TableView, | ||
| traits::TransitionEvaluationContext, | ||
| }; |
There was a problem hiding this comment.
In the snippet provided, a potential issue is found related to edge case handling. When handling the LinearTerm::ConstantUnsigned(value), the operation FieldElement::<A>::from(*value) is used without any check for large values which may not fit within the bounds of FieldElement, depending on the field size. Mathematical Correctness: Ensure that conversion from an unsigned integer to a FieldElement handles large values appropriately and does not truncate or overflow unexpectedly, which could lead to incorrect computation results. Performance: Consider reviewing if FieldElement::<A>::from is optimized for performance and handling of input sizes. Security: Make sure that value does not introduce secret-dependent branching if these values are sensitive or secret in the cryptographic context. Code Simplicity and Bugs: If not already handled in other parts of the module, you might want to add validations or assertions to prevent integer overflows or underflows, especially in modular arithmetic contexts. Recommendation: Add checks or handling for large integer conversion, ensure constant-time operations if value is secret, and verify the overall correctness of this operation in the context of library's finite field operations.
| use crate::{prover::ProvingError, trace::TraceTable}; | ||
|
|
||
| use super::types::{ | ||
| BusInteraction, LinearTerm, Multiplicity, LOGUP_CHALLENGE_ALPHA, LOGUP_CHALLENGE_Z, |
There was a problem hiding this comment.
Correctness
- Modular Arithmetic & Field Operations: It's crucial to ensure that the addition
result += FieldElement::<F>::from(*value);does not overflow. Rust's saturating arithmetic isn't implicitly safe for cryptographic cases due to subtle bugs. Here, asFieldElementis a finite field element, the underlying implementation should inherently manage overflow using modulus; confirm this is the case.
Security
- Timing Side-Channels: Verify that all operations on secrets, including this addition, are constant time. It seems there's no secret-dependent branching introduced with this change, which is good.
- Zeroization: Ensure any temporary computations related to secrets are correctly zeroized after use.
Performance
- Unnecessary Allocations: Consider if
FieldElement::<F>::from(*value);results in unnecessary allocations. Assess if the implementation offromefficiently handles conversion without excess.
Bugs & Errors
- The operation seems to be directly reliant on a single constructed
FieldElement. Ensure no implicit unwraps or panics occur here.
Code Simplicity
- The code introduces the
ConstantUnsigned(value)case, which appears to be straightforward. Verify that this doesn't duplicate logic found elsewhere in the traces.
Overall, verify correctness and efficiency aspects in the surrounding code context for complete analysis. Given these concerns, performing a detailed inspection of related components in the codebase would be beneficial before merging.
| // Linear Term and Bus Value | ||
| // ============================================================================= | ||
|
|
||
| /// A term in a linear combination of column values and constants. |
There was a problem hiding this comment.
Correctness:
- Mathematical operations: The modification introduces a new
ConstantUnsigned(u64)variant. Ensure all areas usingLinearTerm::Constantfor calculation are updated to handleConstantUnsignedaccurately. - Edge cases: Ensure that edge cases involving maximum and minimum values of i64 and u64 are properly handled, especially during the conversion in mathematical operations.
Security:
- No specific security concerns were directly identified in this snippet. However, ensure that wherever
FieldElementoperations occur, they are implemented in a constant-time manner to mitigate timing side-channel vulnerabilities.
Performance:
- No immediate performance issues are detected from this snippet. However, ensure that conversions or operations involving u64 and i64 don't introduce unnecessary overhead or additional allocations.
Bugs & Errors:
- Potential panics or unwraps: The code appears not to have any detected unwraps or explicit panics in this snippet, but ensure that all arithmetic operations handle overflow/underflow gracefully.
Code Simplicity:
- Complexity: The introduction of
ConstantUnsignedadds complexity. Ensure this distinction is necessary and used consistently across the codebase to avoid potential logic errors.
Consider reviewing how different LinearTerm variants are handled throughout the codebase to ensure consistency and correctness, particularly focusing on areas that involve conversion or arithmetic between signed and unsigned types. Verify that all new variants are tested appropriately to handle their specific use cases and edge cases.
|
@greptile review |
Kimi AI ReviewHere are my reviews of the provided PR diff:
|
|
|
||
| // ============================================================================= | ||
| // Lookup Term Constraint (degree 2) | ||
| // ============================================================================= |
There was a problem hiding this comment.
Correctness
- Mathematical Operations: The use of
unsigned_abs()in this context is correct if the intention is to handle all negative values properly within unsigned modular arithmetic. However, it's crucial thatcoefficientandvalueare sufficiently small such that their absolute values fit within au64, else this cast might lead to incorrect behavior due to truncation without a compile-time or runtime warning. Ensure there are checks or document the input constraints clearly.
Security
- Timing Side-Channels: Ensure that
FieldElement::from()is constant time if input could be secret data. - Zeroization: No evidence here to suggest zeroization is necessary or is incorrectly handled, but ensure any sensitive data is zeroized after use.
Performance
- The code uses
FieldElement::from(value.unsigned_abs()), which is efficient if these conversions don't involve costly operations generally, but check if any unnecessary conversions can be avoided.
Bugs & Errors
- No direct panics or unwraps are evident here, but ensure that wherever
valueandcoefficientoriginate from handles errors/exceptions cleanly in edge cases. - Integer Overflow/Underflow: The use of
unsigned_abs()should be thoroughly evaluated to guarantee that no overflow or underflow occurs, especially given the conversion tou64.
Code Simplicity
- The change simplifies the code slightly by using
unsigned_abs(). However, it assumesvalueandcoefficientare within the correct bounds to avoid overflow. Ensure that these assumptions are documented or validated at runtime.
| /// Each row contains: `term[i] = sign * multiplicity[i] / fingerprint[i]` | ||
| /// | ||
| /// where: | ||
| /// - `fingerprint[i] = z - (bus_id*α^0 + v[0]*α^1 + v[1]*α^2 + ...)` |
There was a problem hiding this comment.
Correctness:
- The use of
unsigned_abs()in this context is potentially incorrect ifvalueorcoefficientcould bei128::MIN, asunsigned_abs()might result in a panic due to the absolute value exceedingi128::MAX. This should be checked and handled appropriately to avoid panic and ensure correctness.
Security:
- There are no indications of constant-time operations or zeroization for secret data. These should be carefully reviewed to ensure no timing side-channels or data leakage occur.
- No details on randomness and hash functions suggest that those aspects might need further scrutiny if they're outside the provided code change.
Performance:
- No explicit issues identified in this snippet, but it should be noted that handling field elements carefully can avoid unnecessary allocations.
Bugs & Errors:
- As mentioned,
unsigned_abs()can panic for the minimum value of signed integers, which may lead to an unexpected crash. Proper error checking and handling should be implemented.
Code Simplicity:
- The use of
unsigned_abs()simplifies the expression by removing negation logic, but requires careful consideration given its potential for panics. An alternative approach should be considered to maintain both simplicity and safety.
| pub const LOGUP_CHALLENGE_Z: usize = 0; | ||
|
|
||
| /// Index of the `alpha` (α) challenge in the LogUp challenges vector. | ||
| /// Used as the base for linear combination of row values. |
There was a problem hiding this comment.
Correctness:
- Mathematical operations: The change from using negative conversion with casting to
unsigned_absis intended to ensure positive values are correctly handled. However, it is important to explicitly verify thatunsigned_abs()correctly translates the intended mathematical operation in negative contexts according to the library's specifications. - Edge cases: Ensure that when
*coefficientand*valueare exactly zero or negative, the behavior is consistent with expected zero cases in the context ofFieldElementto prevent logical errors.
Security:
- Timing side-channels: No explicit timing side-channel analysis is covered by this diff, but confirming that
unsigned_abs()does not introduce branching that could leak secret information based on sign is necessary.
Performance:
- Unnecessary allocations: The current changes do not introduce additional allocations and seem to streamline conversion with
unsigned_abs()providing potential micro-optimizations.
Bugs & Errors:
- Potential panics or unwraps: The use of
as u64andunsigned_abs()should be inspected to ensure there are no edge cases that could lead to runtime panics, particularly with very large negative values that could overflow when converted to unsigned.
Code Simplicity:
- The simplification by using
unsigned_abs()improves readability but warrants verification that the semantic changes (related to handling of negatives) have been cross-checked with domain rules forFieldElement.
Before merging, it is advisable to perform a comprehensive set of unit tests that cover edge cases involving negative numbers, zeros, and large values to verify both correctness and no unintended security implications.
Greptile OverviewGreptile SummaryThis PR adds a reusable LogUp lookup argument module to the STARK prover with a declarative bus interaction API. Users define bus interactions (senders/receivers with multiplicities and values), and the system automatically generates auxiliary trace columns, degree-2 term constraints, degree-1 accumulation constraints, and boundary conditions. Major changes:
Implementation notes:
Tests:
Confidence Score: 4/5
|
| Filename | Overview |
|---|---|
| crates/provers/stark/src/lookup/constraints.rs | Core LogUp constraint logic with potential wrap-around issue in accumulated constraint |
| crates/provers/stark/src/lookup/air.rs | Main AIR wrapper with LogUp support, includes comprehensive tests |
| crates/provers/stark/src/lookup/trace_builder.rs | Auxiliary trace builders with known performance issue from repeated cloning |
| crates/provers/stark/src/lookup/types.rs | Type definitions for bus interactions, multiplicities, and linear terms - clean |
| crates/provers/stark/src/trace.rs | Added allocate_aux_table method for dynamic aux column allocation |
| crates/math/src/field/fields/u64_goldilocks_field.rs | Added ByteConversion, AsBytes, and HasDefaultTranscript impls for Goldilocks |
Sequence Diagram
sequenceDiagram
participant User as User AIR
participant AirWithLogUp
participant TraceBuilder
participant Prover
participant Verifier
User->>AirWithLogUp: new(interactions, constraints)
AirWithLogUp->>AirWithLogUp: Add LookupTermConstraint per interaction
AirWithLogUp->>AirWithLogUp: Add LookupAccumulatedConstraint
Prover->>AirWithLogUp: build_rap_challenges()
AirWithLogUp-->>Prover: [z, alpha]
Prover->>AirWithLogUp: build_auxiliary_trace(trace, challenges)
AirWithLogUp->>TraceBuilder: build_logup_term_column() for each interaction
loop For each row
TraceBuilder->>TraceBuilder: fingerprint = z - (bus_id*α⁰ + v₀*α¹ + v₁*α² + ...)
TraceBuilder->>TraceBuilder: term = sign * multiplicity / fingerprint
end
TraceBuilder->>TraceBuilder: build_accumulated_column()
loop For each row
TraceBuilder->>TraceBuilder: acc[i] = acc[i-1] + Σ terms[i]
end
AirWithLogUp-->>Prover: Ok(())
Prover->>AirWithLogUp: boundary_constraints()
AirWithLogUp-->>Prover: acc[N-1] = 0
Prover->>AirWithLogUp: transition_constraints()
loop For each interaction
AirWithLogUp-->>Prover: term[i] * fingerprint[i] = sign * multiplicity[i]
end
AirWithLogUp-->>Prover: acc[i+1] - acc[i] - Σ terms[i+1] = 0
Prover->>Verifier: proof
Verifier->>Verifier: Verify all constraints hold
| } | ||
|
|
||
| // Build term columns | ||
| let main_segment_cols = trace.columns_main(); |
There was a problem hiding this comment.
Calling columns_main() in the loop creates a full clone of the main trace for each interaction. This is O(interactions × trace_size) copying. Consider passing a reference to trace.main_table directly or caching the result outside the loop.
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/air.rs
Line: 172:172
Comment:
Calling `columns_main()` in the loop creates a full clone of the main trace for each interaction. This is O(interactions × trace_size) copying. Consider passing a reference to `trace.main_table` directly or caching the result outside the loop.
How can I resolve this? If you propose a fix, please make it concise.| /// constraints that ensure multiplicity columns contain correct values (e.g., | ||
| /// range checks, boolean checks, or consistency with actual occurrence counts). | ||
| /// Without these constraints, a malicious prover could set arbitrary multiplicities | ||
| /// and break bus balance soundness. |
There was a problem hiding this comment.
The LogUp module doesn't constrain multiplicity values - users must add their own constraints. Consider adding a runtime check in debug builds to warn if multiplicity columns contain unexpected values (e.g., negative or out-of-range).
Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/types.rs
Line: 139:142
Comment:
The LogUp module doesn't constrain multiplicity values - users must add their own constraints. Consider adding a runtime check in debug builds to warn if multiplicity columns contain unexpected values (e.g., negative or out-of-range).
<sub>Note: If this suggestion doesn't match your team's coding style, reply to this and let me know. I'll remember it for next time!</sub>
How can I resolve this? If you propose a fix, please make it concise.
Kimi AI ReviewReview of
|
Kimi AI ReviewHere are my feedback and comments on the PR diff:
Overall, the changes seem to be adding support for the LogUp protocol, which is useful for STARK proofs. However, there are some areas that could be improved with additional documentation and error checking. |
* Feat/sumcheck optimizations (#1084) * feat(sumcheck): Add optimized provers and advanced algorithms - Add VSBW13 streaming prover (O(2^n) vs O(n*2^2n)) - Add parallel prover with rayon - Add sparse prover for polynomials with few non-zero entries - Add Blendy memory-efficient prover - Add small field optimizations - Add batched proving - Add Metal GPU stubs * feat(sumcheck): Add Metal GPU backend and fix sparse prover - Implement full Metal GPU prover with compute shaders - Fix sparse prover transcript format for verification - Add clippy fixes - Add Metal dependencies (optional) * docs(sumcheck): Add paper references and comprehensive tests - Add academic paper citations with authors and ePrint links - Add 16 new tests bringing total to 89 - Test coverage for all prover variants * docs(sumcheck): Add repository references to all prover implementations Add links to implementations consulted for each algorithm: - prover_optimized: arkworks/sumcheck, microsoft/Spartan, HyperPlonk - sparse_prover: a16z/jolt, microsoft/Spartan2, nexus-xyz/nexus-zkvm - blendy: arkworks/sumcheck, scroll-tech/ceno - small_field: Plonky3, binius, stwo - prover_parallel: arkworks/sumcheck, microsoft/Nova, rayon-rs - metal/prover: lambdaworks, Icicle, metal-rs * refactor(sumcheck): Extract common utilities and reduce code duplication - Add common.rs module with shared prover utilities - Create SumcheckProver trait as unified interface for all implementations - Extract run_sumcheck_protocol() to handle transcript operations centrally - Add validation helpers: validate_factors(), validate_num_vars(), check_round_bounds() - Add computation utilities: apply_challenge_to_evals(), compute_round_sums_single() - Refactor all provers to implement SumcheckProver trait - Net reduction of ~270 lines while preserving all functionality - All 95 tests pass * fix(stark): Return error when multi_prove receives empty airs Previously multi_prove would panic by calling unwrap() on None when the airs vector was empty. Now it returns ProvingError::EmptyAirs for proper error handling. * fix(math): Guard polynomial division and xgcd against zero divisors - long_division_with_remainder now asserts the divisor is non-zero - xgcd now panics with clear message when both inputs are zero - Added documentation about panic conditions * fix(stark): Validate grinding_factor to prevent overflow - Add assertion that grinding_factor must be <= 64 - Handle grinding_factor == 0 case explicitly (any nonce is valid) - Prevents undefined behavior from 1 << 64 shift - Prevents underflow when grinding_factor > 64 * fix(crypto): Guard sample_u64 against zero upper_bound Add assertion to prevent division by zero when upper_bound is 0 in both DefaultTranscript and StoneProverTranscript implementations. * perf(math): Pre-allocate vector in DenseMultilinearPolynomial::merge Calculate total size upfront and use with_capacity to avoid repeated reallocations when merging large polynomials. * perf(stark): Optimize Table::columns with pre-allocation - Pre-allocate all column vectors upfront with known capacity - Use single pass through data instead of nested iteration - Reduces allocation overhead for large traces * style: Apply cargo fmt * fix clippy * fix fmt * check batch instance has a factor so that it doesn't panic * fix bug field operations in metal * fix bug: add overflow in metal * update readme * fix(sumcheck): fix Blendy stage table bug, remove dead code, clean up tests - Fix Blendy compute_stage_table missing prefix variable iteration, which produced invalid proofs for multi-stage configurations - Remove unused fields and imports (batching_coeff, num_instances, num_stages, remaining_vars, current_round, rayon placeholders) - Fix batched verifier duplicate code in if/else branches - Fix test silently accepting errors via println - Replace metal prover unwrap calls with let-else pattern - Add verification tests for Blendy proofs (2-stage, 3-stage) * fix clippy --------- Co-authored-by: Nicole <nicole.graus@lambdaclass.com> * fix(stark): fix vacuous LogUp accumulated constraint and dynamic boundary The LookupAccumulatedConstraint (degree 1) had end_exemptions = 0, making it vacuous: a degree-1 constraint polynomial (degree N-1) divided by a degree-N zerofier can only be the zero polynomial, so the verifier learns nothing. Changed to end_exemptions = 1 so the quotient is a meaningful constant. Also made the accumulated column boundary value dynamic (stored via RwLock after trace building) instead of hardcoded zero, supporting multi-table systems where individual partial sums are non-zero. --------- Co-authored-by: Nicole <nicole.graus@lambdaclass.com>
|
|
||
| impl<F, E, B, PI> AirWithLogUp<F, E, B, PI> | ||
| where | ||
| F: IsFFTField + IsSubFieldOf<E> + Send + Sync + 'static, |
There was a problem hiding this comment.
Correctness
- The code seems to be handling the accumulator's final value correctly by storing it in
acc_boundary_value. However, it's crucial to ensure that any arithmetic involving storage and retrieval of this value is performed within the field to avoid any incorrect interpretations of zero or non-zero states due to potential differences in field representation.
Security
- RwLock Use: While
RwLockallows for concurrent read access, care should be taken with locking since writing operations (viawrite().unwrap()) could potentially introduce race conditions if access is not adequately controlled. Consider if there is a genuine concurrent read/write requirement, as sensitive data access should ideally be minimized and synchronized. - Potential Challenges with Secret-dependent Logic: Ensure that all accesses and operations involving
acc_boundary_valueare constant-time, especially if they influence any subsequent cryptographic operations. Make sure any secret data involved is consistently zeroized after use.
Performance
- No obvious performance issues are visible in the diff related to unnecessary allocations, but check if loading/copying operations of
FieldElementare optimized or could be replaced with references where possible.
Bugs & Errors
- Use of
unwrap(): There is a use ofunwrap()on a lock which can panic if poisoned. Consider handling this gracefully, especially in contexts where panics could propagate or cause undefined behavior. - Potential Race Condition: Investigate if concurrent operations could lead to a race condition with
acc_boundary_value, particularly in a multi-threaded environment.
Code Simplicity
- The code additions are concise and seem appropriately abstracted for the operations being described. Ensure that the additional logic regarding
acc_boundary_valuechecks does not overly complicate the interface or internal state management of the object.
Summary
Overall, the changes incorporate a sensible mechanism for handling different bus states using the acc_boundary_value. However, without full visibility into concurrency and secret management elsewhere in the system, the use and management of locks and potential for race conditions remain concerns. Ensure any public interfaces the code touches maintain security and thread safety.
| /// Verifies: `term[i] * fingerprint[i] - sign * multiplicity[i] = 0` | ||
| /// | ||
| /// This is degree 2 because it multiplies the aux column (`term`) by | ||
| /// the fingerprint (which is linear in main trace values). |
There was a problem hiding this comment.
Concerns from the Code Review:
-
Mathematical Correctness:
- The change to
end_exemptionsfrom0to1prompts a mathematical concern because this affects the degree of the zerofier and the quotient polynomial. Ensure that this exemption properly aligns with the underlying mathematical proof requirements. However, the comment added clarifies the need for this change, which improves soundness. Further verification of its correctness with extensive tests or proofs is recommended.
- The change to
-
Security:
- There are no explicit details in the displayed code about data handling, making it challenging to assess security. Verify the context around randomness generation for cryptographic security and ensure constant-time operations in parts dealing with secret data.
- Verify if there are mechanisms for zeroization of larger sensitive data sets.
-
Performance:
- The current change is not directly related to performance, but ensure overall that polynomial evaluations and field operations are optimized.
- Check for unnecessary memory allocations elsewhere, especially within frequently called operations.
-
Bugs & Errors:
- No direct issues visible related to panics or unwraps in this snippet; however, confirm if the broader scope of the code is safeguarded against such risks.
- Make sure that bounds checking is comprehensive elsewhere in the implementation to avoid potential overflows or off-by-one errors.
-
Code Simplicity:
- The code adjustments themselves seem straightforward. However, ensure complex logic is well-documented and refactored at later stages.
Summary:
The recent change for end_exemptions seems justified by the added comment and theoretical explanation. However, without further context on execution and tests verifying this change correctly, a meticulous audit is warranted. Key areas like security and mathematical correctness need further validation across the related implementation parts to confirm overall code integrity.
Kimi AI ReviewHere are my reviews for the provided PR diff:
|
|
@greptile |
Greptile OverviewGreptile SummaryThis PR adds a reusable LogUp lookup argument module to the STARK prover with a declarative bus interaction API. Users define Key changes:
Critical issues identified in previous review threads:
Confidence Score: 2/5
|
| Filename | Overview |
|---|---|
| crates/provers/stark/src/lookup/types.rs | New file defining core LogUp types (BusInteraction, BusValue, Multiplicity, LinearTerm) with clear abstractions and comprehensive documentation |
| crates/provers/stark/src/lookup/constraints.rs | Implements term and accumulated constraints with degree-1 accumulated constraint having end_exemptions=1 to avoid vacuous constraint |
| crates/provers/stark/src/lookup/air.rs | Implements AirWithLogUp wrapper that auto-generates aux columns and constraints; has critical boundary constraint tautology issue and aux allocation bug |
| crates/provers/stark/src/lookup/trace_builder.rs | Builds term and accumulated columns for LogUp; has alpha power mismatch between prover and verifier, causing incorrect fingerprints |
Sequence Diagram
sequenceDiagram
participant User
participant AirWithLogUp
participant TraceBuilder
participant Constraints
participant Prover
User->>AirWithLogUp: new(interactions, constraints)
AirWithLogUp->>AirWithLogUp: Generate LogUp constraints
Note over AirWithLogUp: Adds LookupTermConstraint for each interaction<br/>Adds LookupAccumulatedConstraint
User->>Prover: prove(air, trace)
Prover->>AirWithLogUp: build_rap_challenges(transcript)
AirWithLogUp-->>Prover: [z, alpha]
Prover->>AirWithLogUp: build_auxiliary_trace(trace, challenges)
AirWithLogUp->>TraceBuilder: build_logup_term_column (per interaction)
Note over TraceBuilder: Compute fingerprint = z - (bus_id + v₀·α + v₁·α² + ...)<br/>Set term[i] = sign * multiplicity[i] / fingerprint[i]
TraceBuilder-->>AirWithLogUp: Term column filled
AirWithLogUp->>TraceBuilder: build_accumulated_column
Note over TraceBuilder: acc[i] = acc[i-1] + Σ terms[i]
TraceBuilder-->>AirWithLogUp: Accumulated column filled
AirWithLogUp->>AirWithLogUp: Store final_accumulated for boundary
AirWithLogUp-->>Prover: Aux trace complete
Prover->>AirWithLogUp: boundary_constraints
Note over AirWithLogUp: Constraint: acc[last] = final_accumulated<br/>(stored from witness)
AirWithLogUp-->>Prover: Boundary constraints
Prover->>Constraints: evaluate (on LDE domain)
Note over Constraints: LookupTermConstraint:<br/>term * fingerprint - sign * multiplicity = 0
Note over Constraints: LookupAccumulatedConstraint:<br/>acc[i+1] - acc[i] - Σ terms[i+1] = 0<br/>(end_exemptions = 1)
Constraints-->>Prover: Constraint evaluations
Last reviewed commit: d733b67
…ved to fix LogUp soundness
Kimi AI ReviewThe PR diff introduces significant changes to the
|
| F: IsFFTField + IsSubFieldOf<E> + Send + Sync + 'static, | ||
| E: IsField + Send + Sync + 'static, | ||
| B: BoundaryConstraintBuilder<F, E, PI>, | ||
| PI: Send + Sync, |
There was a problem hiding this comment.
Correctness
- Boundary Constraints: The comment stating
acc[0] = 0 is a verifier-known constant (not prover-derived)suggests critical constraints, but this relies heavily on external validation not shown in the provided code. Ensure the correctness of constraint application relies on properly initialized elements.
Security
- Data Locking: The use of
RwLockforacc_final_valueimplies concurrency. Ensure that concurrent reads/writes will not expose timing side channels.
Bugs & Errors
- Unwrap Risks: The use of
unwraponRwLockcan potentially panic if the lock is poisoned, which can occur if a thread panics while holding the lock. Consider using a more robust error handling strategy to prevent application crashes.
Recommendations
Consider reviewing the implementation of concurrency handling mechanisms to ensure that they do not introduce any unintended side effects or potential panic points. Additionally, validating the sufficiency of boundary constraints and error handling (especially around locking operations) would be beneficial before merging.
|
|
||
| impl LookupTermConstraint { | ||
| pub fn new(interaction: BusInteraction, term_column_idx: usize, constraint_idx: usize) -> Self { | ||
| Self { |
There was a problem hiding this comment.
-
Correctness: The update comments clarify the constraint logic, which is essential for preventing provers from injecting arbitrary offsets. However, it appears there might be a misunderstanding about the indexing or purpose of each term. Double-check to ensure the terms from row
ishould indeed contribute to the sum at rowi+1instead of the current row. This change significantly affects constraint correctness. -
Security: Ensure that all operations involving sensitive data are constant-time, especially in functions related to constraints evaluation in zero-knowledge proof systems, as these could potentially leak information.
-
Performance: There don't seem to be any obvious performance issues in this snippet. The accumulator constraint's logic looks straightforward in terms of computational complexity.
-
Bugs & Errors: The change from
second_step.get_aux_evaluation_elementtofirst_step.get_aux_evaluation_elementrequires careful consideration. Ensure that this reflects the intended operation, as the auxiliary element being fetched at the step can drastically affect the program behavior. Also, confirm that boundaries on loops overterm_columnsare correctly handled to avoid out-of-bounds panics. -
Code Simplicity: The refactoring of comments improves clarity, but ensure consistency between code logic and the documentation. Clarifying distinctions between 'current row' and 'next row', as well as the application of exemptions, helps maintain overall simplicity and readability.
| let trace_len = trace.num_rows(); | ||
|
|
||
| let z = &challenges[LOGUP_CHALLENGE_Z]; | ||
| let alpha = &challenges[LOGUP_CHALLENGE_ALPHA]; |
There was a problem hiding this comment.
Correctness:
- The revised logic for accumulating column in the comment correctly updates
acc[0]to zero and adjusts subsequent indices, which seems consistent with intended mathematical adjustments. However, ensure that all operations on field elements are correct with appropriate modulus checks ifFieldElementdoesn't handle this automatically (though it usually should in a proper implementation). - Double-check that the exclusion of row
N-1terms is correctly constrained by the described degree-2 constraints. Make sure this matches the high-level mathematical specifications you are implementing.
Security:
- Check if the
FieldElementoperations (like addition, zeroing) are performed in constant-time to prevent timing side-channel attacks. - Ensure that all sensitive data handling, like zeroing
accumulatedwould zero the actual underlying data (relying on Rust's drop architecture,FieldElementshould take care of this, assumingFieldElementis implemented with proper security hygiene).
Performance:
- There do not seem to be unnecessary allocations or excessive operations within this snippet – it intelligently aggregates terms from the previous row. Consider parallelizing the addition if it proves to be a performance bottleneck.
- As the loop sums terms from the previous row, ensure there’s unnecessary invocations of clone unless it is explicitly needed for the field operations.
Bugs & Errors:
- The operation
row_sum += trace.get_aux(row - 1, term_col).clone();could potentially panic or read incorrect data ifrowis 0, but you have ensured the loop starts from 1, which mitigates this risk. - Verify all potential points of panic or data corruption, especially in case of out-of-bound access which may depend on
trace.num_rows()and inputs valid toset_auxandget_auxmethods.
Code Simplicity:
- The updating logic within
acc[i] = acc[i-1] + Σ term_columns[i-1]is straightforward and there’s a clear protection against accessing out-of-bound indices with the loop starting at 1. - Address any potentially unclear implementations by improving function abstractions if they grow more complex than shown.
Final Note:
- Despite no explicit detection of errors or major logical flaws here, ensure all upstream components and downstream integrations of these field operations/proofs maintain consistency with module constraints or security assumptions. The note can only address this function's correctness due to the isolated nature of the code snippet with no external context.
| pub const LOGUP_CHALLENGE_Z: usize = 0; | ||
|
|
||
| /// Index of the `alpha` (α) challenge in the LogUp challenges vector. | ||
| /// Used as the base for linear combination of row values. |
There was a problem hiding this comment.
Correctness
- Mathematical Operations: Ensure that the
initial_valuebeing zero is consistently enforced in the code logic, not just documented. It’s crucial to cross-check if this constant zero assumption across relevant operations is adequately coded.
Security
- Zeroization: There's no indication in this snippet that sensitive data (like possibly
final_accumulated) is zeroed out after use. Verify throughout the library if this practice is followed to avoid sensitive information leaks. - Constant-time operations: The snippet doesn’t contain enough information regarding operations on sensitive data, but ensure that field and curve operations are constant-time to prevent timing attacks.
Performance
- Redundant Field Inversions: Be mindful to check other parts of the library for unnecessary inversions as they are expensive operations.
Bugs & Errors
- Potential Panics or Unwraps: Ensure any operations like division or modulus that could panic are checked beforehand to prevent runtime errors.
Code Simplicity
- Documentation Clarity: The comment about
initial_valuebeing always zero is valuable for understanding, but it’s also crucial in the technical implementation logic. Reaffirm that this is programmatically enforced, not just documented.
In summary, while the provided code snippet itself does not present direct issues, it relies on assumptions that must be backed by robustness checks in the codebase, particularly around the enforcement of constant values and potential side-channel vulnerabilities. Addressing these will make it safe to merge.
|
@greptile |
Greptile OverviewGreptile SummaryThis PR adds a reusable LogUp lookup argument module to the STARK prover. The implementation provides a clean abstraction where users declare bus interactions declaratively and get automatic auxiliary trace columns, constraints, and boundary conditions. Key changes:
Recent fixes addressed:
Remaining issues:
Confidence Score: 4/5
|
| Filename | Overview |
|---|---|
| crates/provers/stark/src/lookup/types.rs | Core types for LogUp (BusInteraction, BusValue, Multiplicity, LinearTerm) - well-documented, includes warning about multiplicity constraint responsibility |
| crates/provers/stark/src/lookup/constraints.rs | Term and accumulated constraints with proper end_exemptions=1 for accumulated constraint, iterative alpha computation for efficiency |
| crates/provers/stark/src/lookup/trace_builder.rs | Builds term and accumulated columns - uses alpha.pow(i) in precomputation which could be optimized to iterative multiplication |
| crates/provers/stark/src/lookup/air.rs | AirWithLogUp wrapper - boundary constraints now use verifier-known acc[0]=0, but allocate_aux_table could still overwrite pre-existing data if num_aux_columns mismatches |
Sequence Diagram
sequenceDiagram
participant User as User (AIR implementer)
participant Air as AirWithLogUp
participant Prover as Prover
participant Builder as trace_builder
participant Constraints as Constraint Evaluators
User->>Air: new(interactions, transition_constraints)
Air->>Air: Add LookupTermConstraint for each interaction
Air->>Air: Add LookupAccumulatedConstraint
Prover->>Air: prove(trace)
Air->>Air: build_rap_challenges(transcript)
Note over Air: Sample z, alpha from transcript
Air->>Builder: build_auxiliary_trace(trace, challenges)
Builder->>Builder: allocate_aux_table(num_aux_columns)
loop For each interaction
Builder->>Builder: build_logup_term_column()
Note over Builder: term[i] = sign * m[i] / (z - fingerprint[i])
end
Builder->>Builder: build_accumulated_column()
Note over Builder: acc[0] = 0, acc[i] = acc[i-1] + Σ terms[i-1]
Builder->>Air: Store final_acc = acc[N-1]
Prover->>Air: boundary_constraints()
Note over Air: acc[0] = 0 (verifier-known)<br/>acc[N-1] = final_acc (prover-derived)
Prover->>Constraints: evaluate transition constraints
loop For each term constraint
Constraints->>Constraints: Check: term[i] * fingerprint[i] = sign * m[i]
end
Constraints->>Constraints: Check accumulated: acc[i+1] - acc[i] - Σ terms[i] = 0
Note over Constraints: end_exemptions = 1 (not checked at last row)
Prover->>User: Return proof
Last reviewed commit: b791d9c
|
|
||
| // Precompute powers of alpha | ||
| let num_bus_elements = interaction.num_bus_elements(); | ||
| let alpha_powers: Vec<FieldElement<E>> = (0..num_bus_elements).map(|i| alpha.pow(i)).collect(); |
There was a problem hiding this comment.
inefficient exponentiation in precomputation
| let alpha_powers: Vec<FieldElement<E>> = (0..num_bus_elements).map(|i| alpha.pow(i)).collect(); | |
| let alpha_powers: Vec<FieldElement<E>> = { | |
| let mut powers = Vec::with_capacity(num_bus_elements); | |
| let mut power = FieldElement::<E>::one(); | |
| for _ in 0..num_bus_elements { | |
| powers.push(power.clone()); | |
| power = &power * alpha; | |
| } | |
| powers | |
| }; |
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/trace_builder.rs
Line: 40:40
Comment:
inefficient exponentiation in precomputation
```suggestion
let alpha_powers: Vec<FieldElement<E>> = {
let mut powers = Vec::with_capacity(num_bus_elements);
let mut power = FieldElement::<E>::one();
for _ in 0..num_bus_elements {
powers.push(power.clone());
power = &power * alpha;
}
powers
};
```
How can I resolve this? If you propose a fix, please make it concise.| if num_aux_columns > 0 && trace.num_aux_columns != num_aux_columns { | ||
| trace.allocate_aux_table(num_aux_columns); | ||
| } |
There was a problem hiding this comment.
silent data loss if aux_table already has data but num_aux_columns is stale
If a caller constructs TraceTable with pre-populated aux_table but mismatched num_aux_columns, allocate_aux_table will overwrite all existing witness data with zeros. Consider adding validation:
if trace.aux_table.width() != 0 && trace.aux_table.width() != num_aux_columns {
return Err(ProvingError::WrongParameter(
format!("aux_table already has {} columns but trying to allocate {}",
trace.aux_table.width(), num_aux_columns)
));
}
Prompt To Fix With AI
This is a comment left during a code review.
Path: crates/provers/stark/src/lookup/air.rs
Line: 171:173
Comment:
silent data loss if `aux_table` already has data but `num_aux_columns` is stale
If a caller constructs `TraceTable` with pre-populated `aux_table` but mismatched `num_aux_columns`, `allocate_aux_table` will overwrite all existing witness data with zeros. Consider adding validation:
```
if trace.aux_table.width() != 0 && trace.aux_table.width() != num_aux_columns {
return Err(ProvingError::WrongParameter(
format!("aux_table already has {} columns but trying to allocate {}",
trace.aux_table.width(), num_aux_columns)
));
}
```
How can I resolve this? If you propose a fix, please make it concise.3 participants
Add a reusable LogUp lookup argument as a first-class module in the STARK prover. Users declare bus interactions declaratively and get automatic auxiliary trace columns, constraints, and boundary conditions.