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Killing strategies for model‐based mutation testing
Author(s) -
Aichernig Bernhard K.,
Brandl Harald,
Jöbstl Elisabeth,
Krenn Willibald,
Schlick Rupert,
Tiran Stefan
Publication year - 2015
Publication title -
software testing, verification and reliability
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.216
H-Index - 49
eISSN - 1099-1689
pISSN - 0960-0833
DOI - 10.1002/stvr.1522
Subject(s) - test suite , computer science , random testing , test case , unified modeling language , model based testing , relation (database) , programming language , mutation , test (biology) , semantics (computer science) , reliability engineering , software engineering , data mining , artificial intelligence , machine learning , software , engineering , paleontology , biochemistry , chemistry , regression analysis , biology , gene
Summary This article presents the techniques and results of a novel model‐based test case generation approach that automatically derives test cases from UML state machines. The main contribution of this article is the fully automated fault‐based test case generation technique together with two empirical case studies derived from industrial use cases. Also, an in‐depth evaluation of different fault‐based test case generation strategies on each of the case studies is given and a comparison with plain random testing is conducted. The test case generation methodology supports a wide range of UML constructs and is grounded on the formal semantics of Back's action systems and the well‐known input–output conformance relation. Mutation operators are employed on the level of the specification to insert faults and generate test cases that will reveal the faults inserted. The effectiveness of this approach is shown and it is discussed how to gain a more expressive test suite by combining cheap but undirected random test case generation with the more expensive but directed mutation‐based technique. Finally, an extensive and critical discussion of the lessons learnt is given as well as a future outlook on the general usefulness and practicability of mutation‐based test case generation. Copyright © 2014 John Wiley & Sons, Ltd.