e-Informatica Software Engineering Journal Knowledge Management in Software Testing: A Systematic Snowball Literature Review

Knowledge Management in Software Testing: A Systematic Snowball Literature Review

[1]Krzysztof Wnuk and Thrinay Garrepalli, "Knowledge Management in Software Testing: A Systematic Snowball Literature Review", In e-Informatica Software Engineering Journal, vol. 12, no. 1, pp. 51–78, 2018. [bibtex] [pdf] [doi]

Authors

Krzysztof Wnuk and Thrinay Garrepalli

Abstract

Software testing benefits from the usage of Knowledge Management (KM) methods and principles. Thus, there is a need to adopt KM to the software testing core processes and attain the benefits that it provides in terms of cost, quality, etc.

Aim

To investigate the usage and implementation of KM for software testing. The major objectives include 1. To identify various software testing aspects that receive more attention while applying KM. 2. To analyse multiple software testing techniques, i.e. test design, test execution and test result analysis and highlight KM involvement in these. 3. To gather challenges faced by industry due to the lack of KM initiatives in software testing.

Method

A Systematic Literature Review (SLR) was conducted utilizing the guidelines for snowballing reviews by Wohlin. The identified studies were analysed in relation to their rigor and relevance to assess the quality of the results.

Results

The initial resulting set provided 4832 studies. From these, 35 peer-reviewed papers were chosen among which 31 are primary, and 4 are secondary studies. The literature review results indicated nine testing aspects being in focus when applying KM within various adaptation contexts and some benefits from KM application. Several challenges were identified, e.g., improper selection and application of better-suited techniques, a low reuse rate of software testing knowledge, barriers in software testing knowledge transfer, no possibility to quickly achieve the most optimum distribution of human resources during testing, etc.

Conclusions

The study brings supporting evidence that the application of KM in software testing is necessary, e.g., to increase test effectiveness, select and apply testing techniques. The study outlines the testing aspects and testing techniques that benefit their users.

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