Have we seen enough traces?

Hila Cohen, Shahar Maoz

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

Abstract

Dynamic specification mining extracts candidate specifications from logs of execution traces. Existing algorithms differ in the kinds of traces they take as input and in the kinds of candidate specification they present as output. One challenge common to all approaches relates to the faithfulness of the mining results: how can we be confident that the extracted specifications faithfully characterize the program we investigate? Since producing and analyzing traces is costly, how would we know we have seen enough traces? And, how would we know we have not wasted resources and seen too many of them?In this paper we address these important questions by presenting a novel, black box, probabilistic framework based on a notion of log completeness, and by applying it to three different well-known specification mining algorithms from the literature: k-Tails, Synoptic, and mining of scenario-based triggers and effects. Extensive evaluation over 24 models taken from 9 different sources shows the soundness, generalizability, and usefulness of the framework and its contribution to the state-of-the-art in dynamic specification mining.

Original languageEnglish
Title of host publicationProceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages93-103
Number of pages11
ISBN (Electronic)9781509000241
DOIs
StatePublished - 2015
Event30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015 - Lincoln, United States
Duration: 9 Nov 201513 Nov 2015

Publication series

NameProceedings - 2015 30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015

Conference

Conference30th IEEE/ACM International Conference on Automated Software Engineering, ASE 2015
Country/TerritoryUnited States
CityLincoln
Period9/11/1513/11/15

Keywords

  • Specification Mining

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