Alattin: Mining alternative patterns for detecting neglected conditions

Suresh Thummalapenta, Tao Xie

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

To improve software quality, static or dynamic verification tools accept programming rules as input and detect their violations in software as defects. As these programming rules are often not well documented in practice, previous work developed various approaches that mine programming rules as frequent patterns from program source code. Then these approaches use static defect-detection techniques to detect pattern violations in source code under analysis. These existing approaches often produce many false positives due to various factors. To reduce false positives produced by these mining approaches, we develop a novel approach, called Alattin, that includes a new mining algorithm and a technique for detecting neglected conditions based on our mining algorithm. Our new mining algorithm mines alternative patterns in example form "P1 or P2", where P1 and P 2 are alternative rules such as condition checks on method arguments or return values related to the same API method. We conduct two evaluations to show the effectiveness of our Alattin approach. Our evaluation results show that (1) alternative patterns reach more than 40% of all mined patterns for APIs provided by six open source libraries; (2) the mining of alternative patterns helps reduce nearly 28% of false positives among detected violations.

Original languageEnglish (US)
Title of host publicationASE2009 - 24th IEEE/ACM International Conference on Automated Software Engineering
Pages283-294
Number of pages12
DOIs
StatePublished - 2009
Externally publishedYes
Event24th IEEE/ACM International Conference on Automated Software Engineering, ASE2009 - Auckland, New Zealand
Duration: Nov 16 2009Nov 20 2009

Publication series

NameASE2009 - 24th IEEE/ACM International Conference on Automated Software Engineering

Other

Other24th IEEE/ACM International Conference on Automated Software Engineering, ASE2009
CountryNew Zealand
CityAuckland
Period11/16/0911/20/09

Keywords

  • Alternative patterns
  • Code search
  • Frequent itemset mining

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

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