Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Automated analysis of requirement specifications
ICSE '97 Proceedings of the 19th international conference on Software engineering
Software Inspection
Monolingual Document Retrieval for European Languages
Information Retrieval
Reasoning about inconsistencies in natural language requirements
ACM Transactions on Software Engineering and Methodology (TOSEM)
Information and Software Technology
Guidelines for conducting and reporting case study research in software engineering
Empirical Software Engineering
Design and code inspections to reduce errors in program development
IBM Systems Journal
Modern Information Retrieval
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Practical Machine Learning Tools and Techniques
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Supporting requirements engineers in recognising security issues
REFSQ'11 Proceedings of the 17th international working conference on Requirements engineering: foundation for software quality
CAiSE'11 Proceedings of the 23rd international conference on Advanced information systems engineering
Baselines and bigrams: simple, good sentiment and topic classification
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Short Papers - Volume 2
RE '12 Proceedings of the 2012 IEEE 20th International Requirements Engineering Conference (RE)
Categorizing requirements for a contract-based system integration project
RE '12 Proceedings of the 2012 IEEE 20th International Requirements Engineering Conference (RE)
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Context and motivation: Today's industry specifications, in particular those of the automotive industry, are complex and voluminous. At Mercedes-Benz, a specification and its referenced documents often sums up to 3,000 pages. Question/problem: A common way to ensure the quality in such natural language specifications is technical review. Given such large specifications, reviewers have major problems in finding defects, especially consistency or completeness defects, between requirements with related information, spread over the various documents. Principal ideas/results: In this paper, we investigate two specifications from Mercedes-Benz, whether requirements with related information spread over many sections of many documents can be automatically classified and extracted using text classification algorithms to support reviewers with their work. We further research enhancements to improve these classifiers. The results of this work demonstrate that an automatic classification of requirements for multiple aspects is feasible with high accuracy. Contribution: In this paper, we show how an automatic classification of requirements can be used to improve the review process. We discuss the limitations and potentials of using this approach.