Murazvu, G.; Parkinson, S.; Khan, S.; Liu, N.; Allen, G. A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis Approach. Software 2024, 3, 1–27, doi:10.3390/software3010001.
Murazvu, G.; Parkinson, S.; Khan, S.; Liu, N.; Allen, G. A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis Approach. Software 2024, 3, 1–27, doi:10.3390/software3010001.
Murazvu, G.; Parkinson, S.; Khan, S.; Liu, N.; Allen, G. A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis Approach. Software 2024, 3, 1–27, doi:10.3390/software3010001.
Murazvu, G.; Parkinson, S.; Khan, S.; Liu, N.; Allen, G. A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis Approach. Software 2024, 3, 1–27, doi:10.3390/software3010001.
Abstract
Software testing is an integral yet time-consuming component of software development, and even with capable software testing resources (technology and people), it is still regarded as problematic. Test automation is widely being utilised within the software industry to provide increased testing capacity to ensure high product quality and reliability. In this paper, we are specifically addressing automated testing whereby test cases are manually written. Test automation has its benefits, drawbacks, and impacts on different stages of development. Furthermore, there is often a disconnect between non-technical and technical roles, where non-technical roles (e.g., management) predominantly strive to reduce costs and delivery time whereas technical roles are often driven by quality and completeness. Although it is widely understood that there are challenges with adopting and using automated testing, there is a lack of evidence to understand the different attitudes toward automated testing (AtAT), focusing specifically on why it is not adopted. In this paper, the authors have surveyed practitioners within the software industry from different roles to determine common trends and draw conclusions. A two-stage approach is presented, comprising a comprehensive descriptive analysis and the use of Principle Component Analysis. In total, 81 participants were provided with a series of 22 questions and their responses are compared against job role types and experience levels. In summary, 6 key findings are presented covering expertise, time, cost, tools and techniques, utilisation, organisation, and capacity
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
