A Preliminary Study on the Potential Usefulness of Open Domain Model for Missing Software Requirements Recommendation

TL;DR

This study explores the potential of open domain models to identify missing software requirements by analyzing entity overlaps and regularities, demonstrating promising results with a novel metric.

Contribution

It introduces a preliminary approach using open domain models and a new metric AHME to detect missing requirements, addressing the lack of domain-specific models.

Findings

AHME metric improves requirement detection accuracy

Regularities in entity occurrence aid in identifying missing info

Open domain models can be useful for requirement analysis

Abstract

Completeness is one of the most important attributes of software requirement specifications. Unfortunately, incompleteness is meanwhile one of the most difficult problems to detect. Some approaches have been proposed to detect missing requirements based on the requirement-oriented domain model. However, this kind of models are lacking for lots of domains. Fortunately, the domain models constructed for different purposes can usually be found online. This raises a question: whether or not these domain models are helpful in finding the missing functional information in requirement specification? To explore this question, we design and conduct a preliminary study by computing the overlapping rate between the entities in domain models and the concepts of natural language software requirements and then digging into four regularities of the occurrence of these entities(concepts) based on two example domains. The usefulness of these regularities, especially the one based on our proposed metric AHME (with F2 gains of 146% and 223% on the two domains than without any regularity), has been shown in experiments.