An empirical study on the potential usefulness of domain models for completeness checking of requirements

Abstract

Domain modeling is a common strategy for mitigating incompleteness in requirements. While the benefits of domain models for checking the completeness of requirements are anecdotally known, these benefits have never been evaluated systematically. We empirically examine the potential usefulness of domain models for detecting incompleteness in naturallanguage requirements. We focus on requirements written as "shall"-style statements and domain models captured using UML class diagrams. Through a randomized simulation process, we analyze the sensitivity of domain models to omissions in requirements. Sensitivity is a measure of whether a domain model contains information that can lead to the discovery of requirements omissions. Our empirical research method is case study research in an industrial setting. We have experts construct domain models in three distinct industry domains. We then report on how sensitive the resulting models are to simulated omissions in requirements. We observe that domain models exhibit near-linear sensitivity to both unspecified (i.e., missing) and under-specified requirements (i.e., requirements whose details are incomplete). The level of sensitivity is more than four times higher for unspecified requirements than under-specified ones. These results provide empirical evidence that domain models provide useful cues for checking the completeness of natural-language requirements. Further studies remain necessary to ascertain whether analysts are able to effectively exploit these cues for incompleteness detection.

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

“…Many research focuses on detecting the missing functions based on requirement-oriented domain models [25,26,1]. One possible reason that makes the domain model popular in this field is that it is an explicit representation of the salient concepts in an application domain and the relations between these concepts [12].…”

“…And it also depicts the whole picture of the functions in a domain in a compassed and structured way. In addition, Arora et al [1] conducted an empirical study on the use of domain models for the completeness checking of software requirements and showed that the domain model constructed from software requirements is sufficiently sensitive to the information on missing requirements. However, unfortunately, this kind of software requirements-oriented domain model does not exist for many domains.…”

“…Although there are already some studies about the technologies of automatically extracting domain models from software requirements [1], [34], it is not easy to construct the model from scratch due to two problems. Firstly, some tedious manual work with expertise is required for validating and improving the model for practical usage.…”

“…Even if there are certain overlaps, it is easy to expect the gap must be bigger, i.e., much more concepts of domain models that cannot be found in software requirements. Almost all the existing researches on missing function detection propose detecting the concepts that appear in the domain model but not in requirements [1,25,9]. However, not all missing concepts indicate the missing requirements.…”

Minimal Assumptions Refinement for Realizable Specifications

“…Environment assumptions play a crucial role in the early stages of software design [23]. They are instrumental in the checking of the completeness of user requirements [3], the derivation of software specifications from the requirements [20], the verification of these specifications [17] and in the automatic generation of implementations that achieve them (often known as controller synthesis) [6,11]. In this paper, we focus on their role in software controller synthesis.…”