Abstract
Context: Software specifications are usually written in natural language and may suffer from imprecision, ambiguity, and other quality issues, called thereafter, requirement smells. Requirement smells can hinder the development of a project in many aspects, such as delays, reworks, and low customer satisfaction. From an industrial perspective, we want to focus our time and effort on identifying and preventing the requirement smells that are of high interest. Aim: This paper aims to characterise 12 requirements smells in terms of frequency, severity, and effects. Method: We interviewed ten experienced practitioners from different divisions of a large international company in the safety-critical domain called MBDA Italy Spa. Results: Our interview shows that the smell types perceived as most severe are Ambiguity and Verifiability, while as most frequent are Ambiguity and Complexity. We also provide a set of six lessons learnt about requirements smells, such as that effects of smells are expected to differ across smell types. Conclusions: Our results help to increase awareness about the importance of requirement smells. Our results pave the way for future empirical investigations, ranging from a survey confirming our findings to controlled experiments measuring the effect size of specific requirement smells.
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Gentili, E., Falessi, D. (2024). Characterizing Requirements Smells. In: Kadgien, R., Jedlitschka, A., Janes, A., Lenarduzzi, V., Li, X. (eds) Product-Focused Software Process Improvement. PROFES 2023. Lecture Notes in Computer Science, vol 14483. Springer, Cham. https://doi.org/10.1007/978-3-031-49266-2_27
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