Practitioners’ perceptions on requirements smells

Context: Software specifications are usually written in natural language and may suffer from imprecision, ambiguity, and other quality issues, hereafter referred to as requirement smells. Requirement smells can hinder project development 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 of high interest. We also want to identify the metrics to measure the effect of smells on a software project. Objective: We aim to characterize types of requirement smells in terms of frequency, severity, and effects. To the best of our knowledge, no previous study analysed how frequency, severity, or effects vary across types of smells. Methods: We interview ten experienced practitioners from different divisions of a large international company in the safety–critical domain called MBDA Italy Spa. Then we survey 58 people from the same company to support our findings and extend the analysis to metrics for measuring specific types of requirements smells effects. Results: Our results show that the smell types perceived as most severe are Ambiguity and Unverifiability, while the most frequent are Ambiguity and Incompleteness. We also provide six Findings about requirements smells, such as that the effects of smells are expected to differ across smell types and stages of the project. our study suggests that measuring the effects of requirement smells may necessitate type-specific metrics. Conclusion: Our results contribute to a greater understanding of the importance of addressing requirement smells and provide actionable insights for improving requirement quality in industrial settings. Our results pave the way for future empirical investigations, such as mining project repositories, to measure the specific effect type and size of specific requirements’ smells.