RO  EN
IMI/Publicaţii/CSJM/Ediţii/CSJM v.24, n.2 (71), 2016/

The general prioritization framework

Authors: Alexey Malishevsky
Keywords: Prioritization, regression testing, software testing, prioritization framework, test case prioritization.

Abstract

This paper proposes the general prioritization framework for test case prioritization during regression testing. Regression testing (RT) is done to ensure that modifications have not created new faults or that modifications fulfilled their intended purpose by correctly altering software functionality. Being performed multiple times, RT can have a profound effect on the software budget. The test case prioritization orders test cases for execution to reach a certain objective. Usually, such an objective is to detect faults as early as possible during the testing process. Many prioritization techniques have been developed that successfully reach this objective. However, most of these techniques were developed and studied independently from each other despite the fact that they have many similarities. This article presents the framework that allows to represent known prioritization techniques. Thus, it helps to improve existing and devise new techniques. Also, it allows to implement a single tool that emulates any prioritization technique by just setting the correct parameters. The proposed framework includes the combination/condensation (CC) structure and the structure functions including {\em element combination functions}, {\em condensation functions}, and a {\em super-group combination function}. By defining two such structures together with the corresponding structure functions, one for computing award values and one for their update, any known prioritization technique can be expressed. A general prioritization algorithm is presented that can express any known prioritization technique.

Institution: ESC "Institute for Applied System Analysis"
National Technical University of Ukraine "KPI"
Address: building 35, 37 Prospect Peremohy, 03056, Kyiv, Ukraine
Phone: +380504101177
E-mail:

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License




Fulltext

Adobe PDF document – 0.07 Mb