Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics

Abstract

The quality of requirements is fundamental in engineering projects. Requirements are usually expressed partly or totally in a natural language (NL) format and come from different documents.Their qualities are difficult to analyze manually, especially when hundreds of thousands of them have to be considered. The assistance of software tools is becoming a necessity. In this article, the goal was to develop a set of metrics supported by NL processing (NLP) methods supporting different types of analysis of requirements and especially the dependencies between requirements.An NLP approach is used to extract requirements from text; to analyze their quality, links, similarities, and contradictions; and to cluster them automatically. The analysis framework includes different combinations of methods such as cosine similarity, singular value decomposition, and Kmeans clustering. One objective is to assess the possible combinations and their impacts on detections to establish optimal metrics. Three case studies exemplify and support the validation of the work. Graphs are used to represent the automatically clustered requirements, as well as similarities and contradictions. A new contradiction analysis process that includes a rules-based approach is proposed. Finally, the combined results are presented as graphs, which unveil the semantic relationships between requirements. Subsection 4.8 compares the results provided by the tool and the results obtained from experts. The proposed methodology and network presentation not only support the understanding of the semantics of the requirements but also help requirements engineers to review the interconnections and consistency of requirements systems and manage traceability. The approach is valuable during the early phases of projects when requirements are evolving dynamically and rapidly. K E Y W O R D S contradictions analysis, network representation, requirements management, similarity Systems Engineering. 2018;21:555-575. c 2018 Wiley Periodicals, Inc. 555 wileyonlinelibrary.com/journal/sys AUTHORS' BIOGRAPHIES FAISAL MOKAMMEL is a doctoral student at Aalto University and work at Selko Oy developing a commercial version of the requirement extractor and analyser tool developed during his doctoral thesis. ERIC COATANÉA is tenured professor at Tampere University of Technology and was the initiator of the requirement extractor and analyser project. JOONAS COATANÉA is developer at Selko Oy. MOKAMMEL ET AL. 575 VLADISLAV NENCHEV is software developer and formal logic expert at Selko Oy. ERIC BLANCO is professor at INP Grenoble. MATTI PIETOLA is tenured professor at Aalto University. How to cite this article: Mokammel F, Coatanéa E, Coatanéa J, Nenchev V, Blanco E, Pietola M. Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics. Systems Engineering. 2018;21:555-575. https://doi.

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“…Besides, the two selected papers use different AI techniques and aim to automate two different activities of the design process. In particular, the first paper, presented by Mokammel et al (2018), seeks to automate the generation of a Requirement list. The second paper, presented in Karan and Asadi (2019), has a broader design outcome (i.e.…”

“…To this purpose, the first paper, presented in Mokammel et al (2018), aims to requirement elicitation and treatment thanks to Natural Language processing and to propose a graph representation and clustering of requirements to offer representation allowing to evaluate, to select or to modify the Requirement list As can be seen from Table 3, in general, the level of automation of the Designer-AI Tool interaction presented by the authors is low, except for the "generation" function. In fact, Level 3 is here reached [Designer (Direction) / Computer (Execution)] since the designer has to define the lists of documents to be treated in the analysis.…”