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Automated refinement of models for model-based testing using exploratory testing

Title	Automated refinement of models for model-based testing using exploratory testing
Author	Şahin Gebizli, Ceren, Sözer, Hasan
Publication Date:	2017-09
Publication Place	- Springer International Publishing
Subject	Model-based testing, Exploratory testing, Automated model refinement, Software test automation, Industrial case study
Type	Periodical
Language	English
Digital	Yes
Manuscript	No
Library:	Özyeğin University
Library Asset ID	0963-9314
Record ID	28464c35-310f-4119-a536-7f76fa6ef29f
Library Location	Computer Science
Date	2017-09
Notes	Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text	Model-based testing relies on models of the system under test to automatically generate test cases. Consequently, the effectiveness of the generated test cases depends on models. In general, these models are created manually, and as such, they are subject to errors like omission of certain system usage behavior. Such omitted behaviors are also omitted by the generated test cases. In practice, these faults are usually detected with exploratory testing. However, exploratory testing mainly relies on the knowledge and manual activities of experienced test engineers. In this paper, we introduce an approach and a toolset, ARME, for automatically refining system models based on recorded testing activities of these engineers. ARME compares the recorded execution traces with respect to the possible execution paths in test models. Then, these models are automatically refined to incorporate any omitted system behavior and update model parameters to focus on the mostly executed scenarios. The refined models can be used for generating more effective test cases. We applied our approach in the context of 3 industrial case studies to improve the models for model-based testing of a digital TV system. In all of these case studies, several critical faults were detected after generating test cases based on the refined models. These faults were not detected by the initial set of test cases. They were also missed during the exploratory testing activities.
DOI	10.1007/s11219-016-9338-2
Cilt	25

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Özyeğin University

Automated refinement of models for model-based testing using exploratory testing

Author Şahin Gebizli, Ceren, Sözer, Hasan

Publication Date 2017-09

Publication Place - Springer International Publishing

Subject Model-based testing, Exploratory testing, Automated model refinement, Software test automation, Industrial case study

Type Periodical

Language English

Digital Yes

Manuscript No

Library Özyeğin University

Library Asset ID 0963-9314

Record ID 28464c35-310f-4119-a536-7f76fa6ef29f

Library Location Computer Science

Date 2017-09

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

Sample Text Model-based testing relies on models of the system under test to automatically generate test cases. Consequently, the effectiveness of the generated test cases depends on models. In general, these models are created manually, and as such, they are subject to errors like omission of certain system usage behavior. Such omitted behaviors are also omitted by the generated test cases. In practice, these faults are usually detected with exploratory testing. However, exploratory testing mainly relies on the knowledge and manual activities of experienced test engineers. In this paper, we introduce an approach and a toolset, ARME, for automatically refining system models based on recorded testing activities of these engineers. ARME compares the recorded execution traces with respect to the possible execution paths in test models. Then, these models are automatically refined to incorporate any omitted system behavior and update model parameters to focus on the mostly executed scenarios. The refined models can be used for generating more effective test cases. We applied our approach in the context of 3 industrial case studies to improve the models for model-based testing of a digital TV system. In all of these case studies, several critical faults were detected after generating test cases based on the refined models. These faults were not detected by the initial set of test cases. They were also missed during the exploratory testing activities.

DOI 10.1007/s11219-016-9338-2

Cilt 25