Adopting Use Case Descriptions for Requirements Specification: an Industrial Case Study

TL;DR

This study provides empirical insights into how use case descriptions are adopted in industry, their quality in practice, and the factors influencing their effectiveness in requirements engineering.

Contribution

It offers empirical evidence on the real-world adoption and quality of use case descriptions, highlighting deviations from guidelines and identifying impactful factors.

Findings

Adoption of UC descriptions deviates from textbook recommendations.

Solution-orientation significantly impacts UC quality.

Few properties of requirements engineering influence UC quality.

Abstract

Context: Use case (UC) descriptions are a prominent format for specifying functional requirements. Existing literature abounds with recommendations on how to write high-quality UC descriptions but lacks insights into (1) their real-world adoption, (2) whether these recommendations correspond to actual quality, and (3) which factors influence the quality of UCs. Objectives: We aim to contribute empirical evidence about the adoption of UC descriptions in a large, globally distributed case company. Methods: We surveyed 1188 business requirements of a case company that were elicited from 2020-01-01 until 2024-12-31 and contained 1192 UCs in various forms. Among these, we manually evaluated the 273 template-style UC descriptions against established quality guidelines. We generated descriptive statistics of the format's adoption over the surveyed time frame. Furthermore, we used inferential statistics to determine (a) how properties of the requirements engineering process affected the UC quality and (b) how UC quality affects subsequent software development activities. Results and Conclusions: Our descriptive results show how the adoption of UC descriptions in practice deviates from textbook recommendations. However, our inferential results suggest that only a few phenomena like solution-orientation show an actual impact in practice. These results can steer UC quality research into a more relevant direction.