Open AccessOSFPMiner: An Optimal Weighted Traversal Software Patterns Miner Based on Complex Network
Author(s) -
He Haitao,
Shan Chun,
He Hongdou,
Zhao Guyu,
Zhang Yangsen,
Tian Xiangmin
Publication year - 2020
Publication title -
chinese journal of electronics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.267
H-Index - 25
eISSN - 2075-5597
pISSN - 1022-4653
DOI - 10.1049/cje.2020.01.002
Subject(s) - tree traversal , computer science , graph traversal , pruning , software , dependency graph , data mining , dependency (uml) , graph , theoretical computer science , parallel computing , algorithm , artificial intelligence , programming language , agronomy , biology
The weighted traversal pattern is important in software system for a better understanding of the internal structure and behavior of software. To mine important patterns of software, a complex network‐based Optimal Software Fault Patterns Miner is presented. By analyzing the multiple execution traces of software and the relations among functions, we establish the Weighted Software Execution Dependency Graph model ultimately. The traversal database is generated through depth‐first search strategy and the extraction of software path traversals. According to the downward‐closure property, a pruning strategy is adopted by Weighted Frequent Candidate Pattern Tree to cut off more unpromising patterns in advance. A set of important patterns is derived without repeated calculation. The experimental results show that the proposed approach has good performance in the number of weighted frequent candidate patterns and time efficiency.