Can clone detection support quality assessments of requirements specifications?

TL;DR

This paper explores how clone detection techniques, traditionally used for source code, can be applied to requirements specifications to identify redundancy and support quality assessments in software engineering.

Contribution

It demonstrates the feasibility of using clone detection on natural language requirements to evaluate redundancy, a key quality aspect, through a large-scale case study.

Findings

Significant redundancy was found in real-world requirements specifications.

Existing clone detection approaches can be adapted for requirements quality assessment.

Redundancy impacts the clarity and maintainability of requirements.

Abstract

Due to their pivotal role in software engineering, considerable effort is spent on the quality assurance of software requirements specifications. As they are mainly described in natural language, relatively few means of automated quality assessment exist. However, we found that clone detection, a technique widely applied to source code, is promising to assess one important quality aspect in an automated way, namely redundancy that stems from copy&paste operations. This paper describes a large-scale case study that applied clone detection to 28 requirements specifications with a total of 8,667 pages. We report on the amount of redundancy found in real-world specifications, discuss its nature as well as its consequences and evaluate in how far existing code clone detection approaches can be applied to assess the quality of requirements specifications in practice.