Yuqing Wang, Mika Mäntylä, Sigrid Eldh, Jouni Markkula, Kristian Wiklund, Tatu Kairi, Päivi Raulamo-Jurvanen, and Antti Haukinen. 2019. A Self-assessment Instrument for Assessing Test Automation Maturity. In Proceedings of the Evaluation and Assessment on Software Engineering (EASE ’19). Association for Computing Machinery, New York, NY, USA, 145–154. DOI:https://doi.org/10.1145/3319008.3319020
A self-assessment instrument for assessing test automation maturity
|Author:||Wang, Yuqing1; Mäntylä, Mika1; Eldh, Sigrid2;|
1M3S, ITEE, University of Oulu, Oulu, Finland
2Ericsson AB Stockholm, Sweden
3Eficode Helsinki, Finland
4M3S, ITEE, University of Oulu Oulu, Finland
5Comiq Helsinki, Finland
|Online Access:||PDF Full Text (PDF, 0.5 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe202001131840
Association for Computing Machinery,
|Publish Date:|| 2020-01-13
Test automation is important in the software industry but self-assessment instruments for assessing its maturity are not sufficient. The two objectives of this study are to synthesize what an organization should focus to assess its test automation; develop a self-assessment instrument (a survey) for assessing test automation maturity and scientifically evaluate it. We carried out the study in four stages. First, a literature review of 25 sources was conducted. Second, the initial instrument was developed. Third, seven experts from five companies evaluated the initial instrument. Content Validity Index and Cognitive Interview methods were used. Fourth, we revised the developed instrument. Our contributions are as follows: (a) we collected practices mapped into 15 key areas that indicate where an organization should focus to assess its test automation; (b) we developed and evaluated a self-assessment instrument for assessing test automation maturity; (c) we discuss important topics such as response bias that threatens self-assessment instruments. Our results help companies and researchers to understand and improve test automation practices and processes.
|Pages:||145 - 154|
23rd Evaluation and Assessment in Software Engineering Conference, EASE 2019; Copenhagen; Denmark; 14-17 April 2019
International Conference on Evaluation and Assessment in Software Engineering
|Type of Publication:||
A4 Article in conference proceedings
|Field of Science:||
113 Computer and information sciences
The authorswould like to thank companies and individuals who participated in interviews. Thiswork has been supported by TESTOMAT Project (ITEA3 ID number 16032), funded by Business Finland under Grant Decision ID 3192/31/2017.
© The Authors 2019. Publication rights licensed to ACM. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in 23rd Evaluation and Assessment in Software Engineering Conference, EASE 2019; Copenhagen; Denmark; 14-17 April 2019, https://doi.org/10.1145/3319008.3319020.