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Published in: Cluster Computing 1/2017

16-01-2017

Multidimensional test coverage analysis: PARADIGM-COV tool

Authors: Ana C. R. Paiva, Liliana Vilela

Published in: Cluster Computing | Issue 1/2017

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Abstract

Currently, software tends to assume increasingly critical roles in our society so assuring its quality becomes ever more crucial. There are several tools and processes of software testing to help increase quality in virtually any type of software. One example is the so called model-based testing (MBT) tools, that generate test cases from models. Pattern Based Graphical User Interface Testing (PBGT) is an example of a MBT new methodology that aims at systematizing and automating the Graphical User Interface (GUI) testing process. It is supported by a Tool (PBGT Tool) which provides an integrated modeling and testing environment for crafting test models based on User Interface Test Patterns (UITP) using a GUI modeling Domain Specific Language (DSL) called PARADIGM. Most of the MBT tools have a configuration phase, where test input data is provided manually by the tester, which influences the quality of the test suite generated. By adding coverage analysis to MBT tools, it is possible to give feedback and help the tester to define the configuration data needed to achieve the most valuable test suite as possible and, ultimately, contribute for increasing the quality of the software. This paper presents a multidimensional test coverage analysis approach and tool (PARADIGM-COV), developed in the context of the PBGT project, that produces coverage information both over the PARADIGM model elements and during test case execution (to identify the parts of the model that were actually exercised). It also presents a case study illustrating the benefits of having multidimensional analysis and assessing the overall test coverage approach.

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Metadata
Title
Multidimensional test coverage analysis: PARADIGM-COV tool
Authors
Ana C. R. Paiva
Liliana Vilela
Publication date
16-01-2017
Publisher
Springer US
Published in
Cluster Computing / Issue 1/2017
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-017-0728-4

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