Combining model-based and risk-based testing for effective test case generation

Name: Combining model-based and risk-based testing for effective test case generation
Author: Şahin Gebizli, C., Metin, D., Sözer, Hasan

İsim	Combining model-based and risk-based testing for effective test case generation
Yazar	Şahin Gebizli, C., Metin, D., Sözer, Hasan
Basım Tarihi:	2015
Basım Yeri	- IEEE
Konu	Memory stress testing, Model-based testing, Riskbased testing, Industrial case study, Test automation, Smart TV
Tür	Belge
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	2-s2.0-84934344142
Kayıt Numarası	0a240089-891d-4491-8997-442f2b4ddf2f
Lokasyon	Computer Science
Tarih	2015
Notlar	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Örnek Metin	Model-based testing employs models of the system under test to automatically generate test cases. In this paper, we propose an iterative approach, in which these models are refined based on the principles of risk-based testing. We use Markov Chains as system models, in which transitions among system states are annotated with probabilities. Initially, these probability values are equal and as such, states have equal chances for being visited by the generated test cases. Memory leaks are monitored during the execution of these test cases. Then, transition probabilities are updated based on the risk that a failure can occur due to the observed memory leaks. We applied our approach in the context of an industrial case study for model-based testing of a Smart TV system. We observed promising results, in which several crash failures were detected after an iteration of model refinement. We aim at automating the whole process based on an adaptation model using the history of recorded memory leaks during previous test executions.
DOI	10.1109/ICSTW.2015.7107464

Kaynağa git Özyeğin Üniversitesi

Aramaya Dön

Özyeğin Üniversitesi

Kaynağa git

Combining model-based and risk-based testing for effective test case generation

Yazar Şahin Gebizli, C., Metin, D., Sözer, Hasan

Basım Tarihi 2015

Basım Yeri - IEEE

Konu Memory stress testing, Model-based testing, Riskbased testing, Industrial case study, Test automation, Smart TV

Tür Belge

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 2-s2.0-84934344142

Kayıt Numarası 0a240089-891d-4491-8997-442f2b4ddf2f

Lokasyon Computer Science

Tarih 2015

Notlar Due to copyright restrictions, the access to the full text of this article is only available via subscription.

Örnek Metin Model-based testing employs models of the system under test to automatically generate test cases. In this paper, we propose an iterative approach, in which these models are refined based on the principles of risk-based testing. We use Markov Chains as system models, in which transitions among system states are annotated with probabilities. Initially, these probability values are equal and as such, states have equal chances for being visited by the generated test cases. Memory leaks are monitored during the execution of these test cases. Then, transition probabilities are updated based on the risk that a failure can occur due to the observed memory leaks. We applied our approach in the context of an industrial case study for model-based testing of a Smart TV system. We observed promising results, in which several crash failures were detected after an iteration of model refinement. We aim at automating the whole process based on an adaptation model using the history of recorded memory leaks during previous test executions.

DOI 10.1109/ICSTW.2015.7107464