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  1. Proceedings of the 8th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering (PASTE '08)
  2. Specification mining of symbolic scenario-based models
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Program analysis for compiler validation
A field study in static extraction of runtime architectures
A non-null annotation inferencer for Java bytecode
Path projection for user-centered static analysis tools
Effective identification of failure-inducing changes: a hybrid approach
Java memory model aware software validation
Specification mining of symbolic scenario-based models
Sharing analysis of arrays, collections, and recursive structures
Addressing common crosscutting problems with Arcum
Towards a more efficient static software change impact analysis method
Elyze: enabling safe parallelism in event-driven servers
Static analysis for inference of explicit information flow
XFindBugs: eXtended FindBugs for AspectJ

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Specification mining of symbolic scenario-based models

Content Provider ACM Digital Library
Author Maoz, Shahar Lo, David
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.
Starting Page 29
Ending Page 35
Page Count 7
File Format PDF
ISBN 9781605583822
DOI 10.1145/1512475.1512482
Language English
Publisher Association for Computing Machinery (ACM)
Publisher Date 2008-11-09
Publisher Place New York
Access Restriction Subscribed
Content Type Text
Resource Type Article
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