Computer Science ›› 2017, Vol. 44 ›› Issue (11): 226-231.doi: 10.11896/j.issn.1002-137X.2017.11.034

Previous Articles     Next Articles

Defects Detection Based on Mining Function Call Sequence Patterns

CUI Zhan-qi, MU Yong-min, ZHANG Zhi-hua and WANG Wei-guang   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Large scale programs usually imply a large number of programming rules.However,if programmers violate those rules in the process of programming,it is possible to cause software defects.The function call rule is one kind of the typical implicit rules in programs.Previous work on mining function rules handle function calls in the body of a function definition as an itemset,and the constraints implied in function call sequences are not utilized,which can lead to high false positive rates.If the function call sequence information is exploited in the process of mining rules,it will effectively improve the accuracy of mining defects.This paper proposed a defect detection approach based on mining function call sequence patterns.In the approach,the suspected defects which violate function call sequence patterns are detected automatically,and the defects with high suspicious degrees are reported.Based on this approach,experiments were carried out in a group of open source projects.The expriment results show that this approach can effectively find defects which violate function call sequence patterns in programs,and reduce false positives.As a result,the overhead of veri-fying suspicious defects are also reduced.

Key words: Function call sequence,Sequence pattern mining,Defects detection

[1] LI M,HUO X.Software Defect Mining Based on Semi-supervised Learning[J].Journal of Data Acquisition and Processing,2016,1(1):56-64.(in Chinese) 黎铭,霍轩.半监督软件缺陷挖掘研究综述[J].数据采集与处理,2016,31(1):56-64.
[2] LI Z,LU S,MYAGMAR S,et al.CP-Miner:a Tool for Finding Copy-Paste and Related Bugs in Operating System Code[C]∥Conference on Symposium on Opearting Systems Design & Implementation.2004:289-302.
[3] LI Z M,ZHOU Y Y.PR-Miner:Automatically Extracting Implicit Programming Rules and Detecting Violations in Large Software Code[C]∥European Software Engineering Conference Held Jointly with,ACM Sigsoft International Symposium on Foundations of Software Engineering.Lisbon,Portugal,2005:306-315.
[4] LU S,PARK S,HU C,et al.MUVI:Automatically Inferring Multi-Variable Access Correlations and Detecting Related Semantic and Concurrency Bugs[C]∥ACM Symposium on Ope-rating Systems Principles 2007(SOSP 2007).Stevenson,Washi-ngton,USA,2010:103-116.
[5] XIE T,PEI J.MAPO:Mining API Usages from Open SourceRepositories[C]∥International Workshop on Mining Software Repositories(MSR 2006).Shanghai,China,2006:54-57.
[6] QU W,JIA Y,JIANG M.Pattern Mining of Cloned Codes inSoftware Systems[J].Information Sciences,2014,259(3):544-554.
[7] HAN J,PEI J,KAMBER M.Data Mining:Concepts and Techniques[M].Elsevier,2011.
[8] HARRINGTON P.Machine Learning in Action[M].Green-wich,CT:Manning,2012.
[9] AGRAWAL R,SRIKANT R.Fast Algorithms for Mining Association Rules in Large Databases[C]∥International Confe-rence on Very Large Data Bases.Morgan Kaufmann Publishers Inc.,1994:487-499.
[10] HAN J.Mining Frequent Patterns without Candidate Generation[J].ACM Sigmod Record,2000,29(2):1-12.
[11] YOUNG M,PEZZE M.Software Testing and Analysis:Process,Principles and Techniques[M].John Wiley & Sons,2007.
[12] MEI H,WANG Q X,ZHANG L,et al.Software Analysis:aRoad Map[J].Chinese Journal of Computers,2009,2(9):1697-1710.(in Chinese) 梅宏,王千祥,张路,等.软件分析技术进展[J].计算机学报,2009,32(9):1697-1710.
[13] AGRAWAL R,SRIKANT R.Mining Sequential Patterns[C]∥IEEE 29th International Conference on Data Engineering.1995:3-14.
[14] SRIKANT R,AGRAWAL R.Mining Sequential Patterns:Ge-neralizations and Performance Improvements[C]∥International Conference on Extending Database Technology:Advances in Database Technology.Springer-Verlag,1996:1-17.
[15] TAN L,ZHANG X,MA X,et al.AutoISES:Automatically Inferring Security Specifications and Detecting Violations[C]∥Conference on Security Symposium.2008:379-394.
[16] TAN L,YUAN D,KRISHNA G,et al./*iComment:Bugs or Bad Comments?*/[C]∥ACM Symposium on Operating Systems Principles 2007(SOSP 2007).Stevenson,Washington,USA,2007:145-158.
[17] TAN L,ZHOU Y,PADIOLEAU Y.aComment:Mining Annotations from Comments and Code to Detect Interrupt Related Concurrency Bugs[C]∥Proceeding of International Conference on Software Engineering.2011:11-20.
[18] YU X M,LIANG B,CHEN H,et al.Path-Sensitive Multi-Varia-ble Access Correlations Mining and Related Source Code Defects Detection[J].Pattern Recognition and Artificial Intelligence,2012,5(4):691-698.(in Chinese) 于秀梅,梁彬,陈红,等.路径敏感的源码关联变量模式挖掘及缺陷检测[J].模式识别与人工智能,2012,25(4):691-698.
[19] ENGLER D,CHEN D Y,HALLEM S,et al.Bugs as Deviant Behavior:a General Approach to Inferring Errors in Systems Code[J].ACM Sigops Operating Systems Review,2010,35(5):57-72.
[20] MAFFORT C,VALENTE M T,BIGONHA M,et al.Mining Architectural Patterns Using Association Rules[C]∥International Conference on Software Engineering and Knowledge Engineering.2013:375-380.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!