Dissertations and theses : Doctoral thesis
Engineering, computing & technology : Computer science
Computational Sciences
Arora, Chetan mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
University of Luxembourg, ​​Luxembourg
Docteur en Informatique
Briand, Lionel mailto
Sabetzadeh, Mehrdad mailto
Le Traon, Yves mailto
Gorschek, Tony
Sawyer, Pete
Nejati, Shiva mailto
[en] Natural Language (NL) is arguably the most common vehicle for specifying requirements. This dissertation devises automated assistance for some important tasks that requirements engineers need to perform in order to structure, manage, and elaborate NL requirements in a sound and effective manner. The key enabling technology underlying the work in this dissertation is Natural Language Processing (NLP). All the solutions presented herein have been developed and empirically evaluated in close collaboration with industrial partners.
The dissertation addresses four different facets of requirements analysis:
• Checking conformance to templates. Requirements templates are an effective tool for improving the structure and quality of NL requirements statements. When templates are used for specifying the requirements, an important quality assurance task is to ensure that the requirements conform to the intended templates. We develop an automated solution for checking the conformance of requirements to templates.
• Extraction of glossary terms. Requirements glossaries (dictionaries) improve the understandability of requirements, and mitigate vagueness and ambiguity. We develop an auto- mated solution for supporting requirements analysts in the selection of glossary terms and their related terms.
• Extraction of domain models. By providing a precise representation of the main concepts in a software project and the relationships between these concepts, a domain model serves as an important artifact for systematic requirements elaboration. We propose an automated approach for domain model extraction from requirements. The extraction rules in our approach encompass both the rules already described in the literature as well as a number of important extensions developed in this dissertation.
• Identifying the impact of requirements changes. Uncontrolled change in requirements presents a major risk to the success of software projects. We address two different dimen- sions of requirements change analysis in this dissertation: First, we develop an automated approach for predicting how a change to one requirement impacts other requirements. Next, we consider the propagation of change from requirements to design. To this end, we develop an automated approach for predicting how the design of a system is impacted by changes made to the requirements.
Fonds National de la Recherche - FnR
FnR ; FNR6911386 > Chetan Arora > > Enhancing the Automation and Accuracy of Requirements Quality Assurance Processes via Disciplined Use of Natural Language > 01/09/2013 > 31/10/2016 > 2013

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