Judith Perera , Ewan Tempero , Yu-Cheng Tu , Kelly Blincoe
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A practitioner survey on Requirements Technical Debt Quantification
Requirements Technical Debt (RTD) is a phenomenon borrowed from the Technical Debt literature that captures the consequences of sub-optimal decisions made concerning software requirements. We report on a survey conducted to understand industry practices and perceptions about RTD quantification.
The survey instrument was designed based on prior work, the RTD Quantification Model (RTDQM), which captures RTD quantification conceptually and serves as a reference point. Our survey employs the Critical Incident Technique (CIT), inquiring practitioners about what RTD instances they encountered. Follow-up questions focused on understanding whether practitioners fixed such RTD instances and whether they quantified model concepts such as the Cost of fixing, the Benefit of fixing, and the Consequences of not fixing. We also sought their opinions on whether quantification supports decision-making.
Our findings suggest that the Benefit of fixing RTD is the concept agreed by most practitioners that it supports decision-making, and is quantified in practice. Practitioners’ preferences regarding the concepts to quantify seem to differ based on the different RTD instances. Survey findings also suggest that the company and individual perspectives regarding the quantification of the concepts differ. Our findings reveal future research avenues that warrant deeper conversations with the industry.
期刊介绍:
The Journal of Systems and Software publishes papers covering all aspects of software engineering and related hardware-software-systems issues. All articles should include a validation of the idea presented, e.g. through case studies, experiments, or systematic comparisons with other approaches already in practice. Topics of interest include, but are not limited to:
•Methods and tools for, and empirical studies on, software requirements, design, architecture, verification and validation, maintenance and evolution
•Agile, model-driven, service-oriented, open source and global software development
•Approaches for mobile, multiprocessing, real-time, distributed, cloud-based, dependable and virtualized systems
•Human factors and management concerns of software development
•Data management and big data issues of software systems
•Metrics and evaluation, data mining of software development resources
•Business and economic aspects of software development processes
The journal welcomes state-of-the-art surveys and reports of practical experience for all of these topics.