Fault Tree is a special tree structure used to test the weakness in a network (for example, web network or computer network). All inner nodes contains a logic gate ("AND" gate or "OR" gate) and the value of any inner node is determined by its logic gate and its children's values (either 1 or 0).
A cut set of the fault tree is a set of leaf values causing the root value equal to 1. A Minimal cut set (MCS) is a cut set with as few 1s as possible in it. If we define broken part of a network as value 1, then minimal cut sets can be used to understand the structural vulnerability of a system.
Finding a minimal cut set for a fault tree is a NP hard problem. However, we can use Monte Carlo algorithm to find a solution or close solution for the minimal cut set (MCS) problem for a fault tree.
Firstly, a raw input file with certain formate is provided (for example, input.txt). An xml file can be generated using parse.py.
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To parse the input into an xml file, in command line type
python parse.py inputfilename -
The xml format will be used to form the defult tree
Secondly, a fault tree is built based on the xml file (generated by parse or provided directly) and then Monte Carlo method is used to get the minimum cut set. In this project, I used two different structures to represent the fault tree structure and realize its functions:
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A tree structure with node (Fault_tree.py): slow
To test the script, in command line type python
python Fault_tree.py xmlfilename 10000 5 -
A dictionary storing nodes with their name as the key (Fault_tree_dict): fast
To test the script, in command line type python
python Fault_tree_dict.py xmlfilename 10000 5
The test cases (input.txt, input1.txt, xml.txt) are in the folder Test_cases. Specially, input.txt and input1.txt are inputs for parse. xml.txt is already in xml format and can serve as the input for Fault_tree and Fault_tree_dict.
- To test parse time, use command
python parse.py inputfilename - To test running time of the script without ouput, use command
python Fault_tree_dict_time.py xmlfilename 10000 0
Thanks Dr.Ennan Zhai for comments. Thanks Zhe (Bob) He for discussion