A conceptual model supporting decision-making for test automation in Agile-based Software Development

Shimza Butt, Saif Ur Rehman Khan, Shahid Hussain, Wen Li Wang

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


With the rise of agile development notion, software test automation is widely adopted by software organizations to reduce the testing time and costs during the software development process. However, it is essential to carefully implement the test automation to ensure the project's success. In the literature, several studies have indicated that decision-making is crucial for the adoption of test automation. For deciding about test automation adoption, several factors, including the skill level of testers, test tool, and development process, need to be considered since automated testing performance heavily depends on the mentioned factors and their interactions. Thus, it is of vital importance to ascertain the factors that influence test automation in the context of Agile-based Software Development (ASD). To accomplish this, we perform a systematic literature review and a questionnaire-based survey. In total, 21 factors are identified that significantly impact test automation in the ASD context. Additionally, the identified factors are categorized into five main classes. Following the identified factors’ assessment, this work proposes a conceptual model that supports agile practitioners in deciding about the adoption of test automation in the context of ASD. Finally, this work validates the proposed model to assess its practical applicability. The validation of the proposed model is accomplished by using an expert-based validation approach. The attained results show that the proposed model supports agile practitioners in estimating the possibility of success when implementing test automation in the ASD context.

Original languageEnglish (US)
Article number102111
JournalData and Knowledge Engineering
StatePublished - Mar 2023

All Science Journal Classification (ASJC) codes

  • Information Systems and Management


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