Scientific Research and Essays

  • Abbreviation: Sci. Res. Essays
  • Language: English
  • ISSN: 1992-2248
  • DOI: 10.5897/SRE
  • Start Year: 2006
  • Published Articles: 2753

Full Length Research Paper

A new conditional invariant detection framework (CIDF)

    Hamid Parvin1, Hamid Alinejad Rokny2, Sajad Parvin1 and Hossein Shirgahi3*        
  1Department of Computer Engineering, Islamic Azad University, Mahdishar Branch, Semnan, Iran. 2Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran. 3Young Researchers Club, Jouybar Branch, Islamic Azad University, Jouybar, Iran.
Email: [email protected]

  •  Accepted: 24 August 2011
  •  Published: 28 February 2013



Software engineering included some different process such as designing, implementing and modifying of software. All these processes are done to have fast developed software as well as reach a high quality, efficient and maintainable software. Invariants help programmer and tester to do most steps of software engineering more easily. Invariants are mostly always true but of course with a specific confidence. Since some invariants are produced in some conditions of program execution and not always, conditional invariants can show the behavior of program so much better. For producing this kind of invariants, it might use some technique of data mining such as association rule mining or using decision tree to obtain rules. So the paper will introduce a new perspective to dynamic invariant detection. Also the feasibility of conditional invariant detection is examined and a framework to extract them is proposed.


Key words: Daikon, invariant, association rules, variable relations, decision tree, program point, data mining, software engineering, predicate, verification.