Model-Based Mutation Testing: on Effectiveness Analysis
| Title | Model-Based Mutation Testing: on Effectiveness Analysis |
|---|---|
| Summary | In this project we compare the effectiveness of some of the existing model-based mutation testing approaches. |
| Keywords | Model Based Testing, Mutation Testing |
| TimeFrame | |
| References | Utting, M., Legeard, B.:Practical Model-Based Testing: A Tools Approach, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2006)
Fevzi Belli, Christof J. Budnik, Axel Hollmann, Tugkan Tuglular, W. Eric Wong, Model-based mutation testing—Approach and case studies, Science of Computer Programming, Volume 120, 1 May 2016, Pages 25-48, ISSN 0167-6423"Utting, M., Legeard, B.:Practical Model-Based Testing: A Tools Approach, Morgan Kaufmann Publishers Inc., San Francisco, CA, USA (2006) Fevzi Belli, Christof J. Budnik, Axel Hollmann, Tugkan Tuglular, W. Eric Wong, Model-based mutation testing—Approach and case studies, Science of Computer Programming, Volume 120, 1 May 2016, Pages 25-48, ISSN 0167-6423" cannot be used as a page name in this wiki. |
| Prerequisites | |
| Author | |
| Supervisor | Mahsa Varshosaz, Mohammad Reza Mousavi |
| Level | Master |
| Status | Open |
Testing is one of the important phased in software development life cycle. As manual testing is usually a laborious and costly process, the effective automation of testing process has become a topic of interest in both academia and industry. Model-Based Testing (MBT) is a software testing technique in which test cases are generated automatically from a model of the system behaviour. Using MBT technique the conformance of the behaviour of an implementation of the system to the specification model is checked by executing test cases. One of the fundamental problems in testing is the huge variety of faults that can be considered. Mutation testing techniques are used for generating faulty versions of software systems by introducing representative faults in the behaviour.
Model-based mutation testing is one of the mutation testing techniques that has been introduced recently. In this technique it is assumed that the system under test is a black box and the source code is not available. Instead of the code, a model of the system is mutated. A set of test cases are generated using the mutants. In this project we investigate the effectiveness of some of the model-based mutation testing algorithms for test case generation.
