Published:
Astrakhan State Technical University, 2020
Published in:
Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics, 2020 (2020) 3, Seite 52-60
Language:
English
DOI:
10.24143/2072-9502-2020-3-52-60
ISSN:
2072-9502;
2224-9761
Origination:
Footnote:
Description:
High quality software systems is an urgent task for any enterprise. Improving quality increases the competitiveness and relevance of software products. One of the tools to ensure quality is testing software systems. This article discusses the basic principles of building an information-advisory system (IAS) of decision support when choosing a method for testing software. The conceptual approaches to testing based on the functional characteristics of software classes are analyzed. When choosing a testing method, it is recommended to take into account not only the financial component, but also the specific characteristics of the tested software system. A list of questions has been developed with the help of which the qualitative properties of software systems are formalized. The list of questions is based on the ISO / IEC 25010: 2011 model. Questionnaires and tables of pairwise comparisons of questions are invited to fill out a group of experts. Questions have equivalent significance with respect to the criterion of “Importance for Automation”. When selecting experts, it is not always possible to create a homogeneous group, therefore, it is proposed to calculate the weighting coefficients of competence of each expert. Based on the data obtained, weights are calculated for answers to questions. Next, the convolution is calculated and, depending on the result, a recommendation is made on choosing the type of testing. The analytical and structural model of IAS is constructed. In the developed software system, a data input subsystem, a subsystem for ranking questions and expert competencies, and a unit for generating the resulting data are allocated. The proposed IAS will make it possible to calculate the competency coefficients of experts, to rank questions according to the degree of importance for testing automation, and to choose the optimal approach to testing software systems.