Practitioners' expectations on automated test generation

• Main Authors: YU, Xiao, LIU, Lei, HU, Xing, KEUNG, Jacky, XIA, Xin, LO, David
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Automated test generation; Practitioners' expectations; Categorical Data Analysis; Numerical Analysis and Computation
• Online Access: https://ink.library.smu.edu.sg/sis_research/9919
• Institution: Singapore Management University

Automated test generation can help developers craft high-quality software tests while mitigating the manual effort needed for writing test code. Despite significant research efforts in automated test generation for nearly 50 years, there is a lack of clarity about what practitioners expect from automated test generation tools and whether the existing research meets their needs. To address this issue, we follow a mixed-methods approach to gain insights into practitioners' expectations of automated test generation. We first conduct the qualitative analysis from semi-structured interviews with 13 professionals, followed by a quantitative survey of 339 practitioners from 46 countries across five continents. We then conduct a literature review of premier venue papers from 2022 to 2024 (in the last three years) and compare current research findings with practitioners' expectations. From this comparison, we outline future research directions for researchers to bridge the gap between automated test generation research and practitioners' expectations.