Efficient test-based model generation for legacy reactive systems

被引：43

作者：

Margaria, T ^{[1
]}

Niese, O ^{[1
]}

Raffelt, H ^{[1
]}

Steffen, B ^{[1
]}

机构：

[1] Univ Gottingen, D-3400 Gottingen, Germany

来源：

NINTH IEEE INTERNATIONAL HIGH-LEVEL DESIGN VALIDATION AND TEST WORKSHOP, PROCEEDINGS | 2004年

关键词：

D O I：

10.1109/HLDVT.2004.1431246

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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 L-Mealy*, 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.

引用

页码：95 / 100

页数：6

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