An algorithm to find critical execution paths of software based on complex network

Author:

Huang Guoyan12,Zhang Bing12,Ren Rong12,Ren Jiadong12

Affiliation:

1. College of Information Science and Engineering, Yanshan University, Qinhuangdao, Hebei 066004, P. R. China

2. The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, Qinhuangdao, Hebei 066004, P. R. China

Abstract

The critical execution paths play an important role in software system in terms of reducing the numbers of test date, detecting the vulnerabilities of software structure and analyzing software reliability. However, there are no efficient methods to discover them so far. Thus in this paper, a complex network-based software algorithm is put forward to find critical execution paths (FCEP) in software execution network. First, by analyzing the number of sources and sinks in FCEP, software execution network is divided into AOE subgraphs, and meanwhile, a Software Execution Network Serialization (SENS) approach is designed to generate execution path set in each AOE subgraph, which not only reduces ring structure's influence on path generation, but also guarantees the nodes' integrity in network. Second, according to a novel path similarity metric, similarity matrix is created to calculate the similarity among sets of path sequences. Third, an efficient method is taken to cluster paths through similarity matrices, and the maximum-length path in each cluster is extracted as the critical execution path. At last, a set of critical execution paths is derived. The experimental results show that the FCEP algorithm is efficient in mining critical execution path under software complex network.

Publisher

World Scientific Pub Co Pte Lt

Subject

Computational Theory and Mathematics,Computer Science Applications,General Physics and Astronomy,Mathematical Physics,Statistical and Nonlinear Physics

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1. Software Crucial Functions Ranking and Detection in Dynamic Execution Sequence Patterns;International Journal of Software Engineering and Knowledge Engineering;2020-05

2. Local Optimization for Clique-Based Overlapping Community Detection in Complex Networks;IEEE Access;2020

3. Mining Important Functions in Software Network by Node Vulnerability;Journal of Physics: Conference Series;2020-01-01

4. A Software Network Model for Software Structure and Faults Distribution Analysis;IEEE Transactions on Reliability;2019-09

5. Mining important nodes in complex software network based on ripple effects of probability;Proceedings of the ACM Turing Celebration Conference - China;2019-05-17

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