Specification mining of symbolic scenario-based models

David Lo*, Shahar Maoz

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many dynamic analysis approaches to specification mining, which extract behavioral models from execution traces, do not consider object identities. This limits their power when used to analyze traces of general object oriented programs. In this work we present a novel specification mining approach that considers object identities, and, moreover, generalizes from specifications involving concrete objects to their symbolic class-level abstractions. Our approach uses data mining methods to extract significant scenario-based specifications in the form of Damm and Harel's live sequence charts (LSC), a formal and expressive extension of classic sequence diagrams. We guarantee that all mined symbolic LSCs are significant (statistically sound) and all significant symbolic LSCs are mined (statistically complete). The technique can potentially be applied to general object oriented programs to reveal expressive and useful reverse-engineered candidate specifications.

Original languageEnglish
Title of host publicationProceedings of the 2008 SIGSOFT/SIGPLAN Workshop on Program Analysis for Software Tools and Engineering, PASTE '08
Pages29-35
Number of pages7
DOIs
StatePublished - 2008
Externally publishedYes
Event2008 SIGSOFT/SIGPLAN Workshop on Program Analysis for Software Tools and Engineering, PASTE '08 - Atlanta, GA, United States
Duration: 9 Nov 200810 Nov 2008

Publication series

NameACM SIGPLAN/SIGSOFT Workshop on Program Analysis for Software Tools and Engineering

Conference

Conference2008 SIGSOFT/SIGPLAN Workshop on Program Analysis for Software Tools and Engineering, PASTE '08
Country/TerritoryUnited States
CityAtlanta, GA
Period9/11/0810/11/08

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