Automated manipulation of natural language requirements, for classification, tracing, defect detection, information extraction, and other tasks, has been pursued by requirements engineering (RE) researchers for more than two decades. Recent technological advancements in natural language processing (NLP) have made it possible to apply this research more widely within industrial settings. This technical briefing targets researchers and practitioners, and aims to give an overview of what NLP can do today for RE problems, and what could do if specific research challenges, also emerging from practical experiences, are addressed. The talk will: survey current research on applications of NLP to RE problems; present representative industrially-ready techniques, with a focus on defect detection and information extraction problems; present enabling technologies in NLP that can play a role in RE research, including distributional semantics representations; discuss criteria for evaluation of NLP techniques in the RE context; outline the main challenges for a systematic application of the techniques in industry. The crosscutting topics that will permeate the talk are the need for domain adaptation, and the essential role of the human-in-the-loop.
Natural Language Requirements Processing: from Research to Practice
Ferrari A
2018
Abstract
Automated manipulation of natural language requirements, for classification, tracing, defect detection, information extraction, and other tasks, has been pursued by requirements engineering (RE) researchers for more than two decades. Recent technological advancements in natural language processing (NLP) have made it possible to apply this research more widely within industrial settings. This technical briefing targets researchers and practitioners, and aims to give an overview of what NLP can do today for RE problems, and what could do if specific research challenges, also emerging from practical experiences, are addressed. The talk will: survey current research on applications of NLP to RE problems; present representative industrially-ready techniques, with a focus on defect detection and information extraction problems; present enabling technologies in NLP that can play a role in RE research, including distributional semantics representations; discuss criteria for evaluation of NLP techniques in the RE context; outline the main challenges for a systematic application of the techniques in industry. The crosscutting topics that will permeate the talk are the need for domain adaptation, and the essential role of the human-in-the-loop.File | Dimensione | Formato | |
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