Efficient test-based model generation for legacy reactive systems

Tiziana Margaria, Oliver Niese, Harald Raffelt, Bernhard Steffen

Research output: Contribution to journalConference articlepeer-review

Abstract

We present the effects of using an efficient algorithm for behavior-based model synthesis which is specifically tailored to reactive (legacy) system behaviors. Conceptual backbone is the classical automata learning procedure L*, which we adapt according to the considered application profile. The resulting learning procedure LMealy*, which directly synthesizes generalized Mealy automata from behavioral observations gathered via an automated test environment, drastically outperforms the classical learning algorithm for deterministic finite automata. Thus it marks a milestone towards opening industrial legacy systems to model-based test suite enhancement, test coverage analysis, and online testing.

Original languageEnglish
Pages (from-to)95-100
Number of pages6
JournalProceedings - IEEE International High-Level Design Validation and Test Workshop, HLDVT
DOIs
Publication statusPublished - 2004
Externally publishedYes
EventProceedings - Ninth IEEE International High-Level Design Validation and Test Workshop, HLDVT'04 - Sonoma Valley, CA, United States
Duration: 10 Nov 200412 Nov 2004

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