Change impact analysis for Natural Language requirements: An NLP approach

Abstract

Requirements are subject to frequent changes as a way to ensure that they reflect the current best understanding of a system, and to respond to factors such as new and evolving needs. Changing one requirement in a requirements specification may warrant further changes to the specification, so that the overall correctness and consistency of the specification can be maintained. A manual analysis of how a change to one requirement impacts other requirements is time-consuming and presents a challenge for large requirements specifications. We propose an approach based on Natural Language Processing (NLP) for analyzing the impact of change in Natural Language (NL) requirements. Our focus on NL requirements is motivated by the prevalent use of these requirements, particularly in industry. Our approach automatically detects and takes into account the phrasal structure of requirements statements. We argue about the importance of capturing the conditions under which change should propagate to enable more accurate change impact analysis. We propose a quantitative measure for calculating how likely a requirements statement is to be impacted by a change under given conditions. We conduct an evaluation of our approach by applying it to 14 change scenarios from two industrial case studies.