Increasing test efficiency by risk-driven model-based testing

Name: Increasing test efficiency by risk-driven model-based testing
Author: Gebizli, C. Ş., Kırkıcı, A., Sözer, Hasan

İsim	Increasing test efficiency by risk-driven model-based testing
Yazar	Gebizli, C. Ş., Kırkıcı, A., Sözer, Hasan
Basım Tarihi:	2018-10
Basım Yeri	- Elsevier
Konu	Model-based testing, Model refinement, Statistical usage testing, Risk-based testing, Industrial case study, Software test automation
Tür	Süreli Yayın
Dil	İngilizce
Dijital	Evet
Yazma	Hayır
Kütüphane:	Özyeğin Üniversitesi
Demirbaş Numarası	0164-1212
Kayıt Numarası	1138610f-4ad1-4197-afee-a79308564506
Lokasyon	Computer Science
Tarih	2018-10
Notlar	Vestel Electronics ; Turkish Ministry of Science, Industry and Technology
Örnek Metin	We introduce an approach and a tool, RIMA, for adapting test models used for model-based testing to augment information regarding failure risk. We represent test models in the form of Markov chains. These models comprise a set of states and a set of state transitions that are annotated with probability values. These values steer the test case generation process, which aims at covering the most probable paths. RIMA refines these models in 3 steps. First, it updates transition probabilities based on a collected usage profile. Second, it updates the resulting models based on fault likelihood at each state, which is estimated based on static code analysis. Third, it performs updates based on error likelihood at each state, which is estimated with dynamic analysis. The approach is evaluated with two industrial case studies for testing digital TVs and smart phones. Results show that the approach increases test efficiency by revealing more faults in less testing time.
DOI	10.1016/j.jss.2018.06.080
Cilt	144

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Increasing test efficiency by risk-driven model-based testing

Yazar Gebizli, C. Ş., Kırkıcı, A., Sözer, Hasan

Basım Tarihi 2018-10

Basım Yeri - Elsevier

Konu Model-based testing, Model refinement, Statistical usage testing, Risk-based testing, Industrial case study, Software test automation

Tür Süreli Yayın

Dil İngilizce

Dijital Evet

Yazma Hayır

Kütüphane Özyeğin Üniversitesi

Demirbaş Numarası 0164-1212

Kayıt Numarası 1138610f-4ad1-4197-afee-a79308564506

Lokasyon Computer Science

Tarih 2018-10

Notlar Vestel Electronics ; Turkish Ministry of Science, Industry and Technology

Örnek Metin We introduce an approach and a tool, RIMA, for adapting test models used for model-based testing to augment information regarding failure risk. We represent test models in the form of Markov chains. These models comprise a set of states and a set of state transitions that are annotated with probability values. These values steer the test case generation process, which aims at covering the most probable paths. RIMA refines these models in 3 steps. First, it updates transition probabilities based on a collected usage profile. Second, it updates the resulting models based on fault likelihood at each state, which is estimated based on static code analysis. Third, it performs updates based on error likelihood at each state, which is estimated with dynamic analysis. The approach is evaluated with two industrial case studies for testing digital TVs and smart phones. Results show that the approach increases test efficiency by revealing more faults in less testing time.

DOI 10.1016/j.jss.2018.06.080

Cilt 144