Defect type and its impact on the growth curve
ICSE '91 Proceedings of the 13th international conference on Software engineering
Exploring Requirements: Quality Before Design
Exploring Requirements: Quality Before Design
AbstFinder, A Prototype Natural Language Text Abstraction Finder for Use in Requirements Elicitation
Automated Software Engineering
Improving Requirements Tracing via Information Retrieval
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
Helping Analysts Trace Requirements: An Objective Look
RE '04 Proceedings of the Requirements Engineering Conference, 12th IEEE International
Measuring the Expressiveness of a Constrained Natural Language: An Empirical Study
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
Enriching the knowledge sources used in a maximum entropy part-of-speech tagger
EMNLP '00 Proceedings of the 2000 Joint SIGDAT conference on Empirical methods in natural language processing and very large corpora: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 13
User guidance for creating precise and accessible property specifications
Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering
What Every Engineer Should Know about Software Engineering (What Every Engineer Should Know)
What Every Engineer Should Know about Software Engineering (What Every Engineer Should Know)
Improving the Accuracy of Space Mission Software Anomaly Frequency Estimates
SMC-IT '09 Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology
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Most research works have found that an important root cause of software project failure comes from the requirements; their quality has an important impact over other artifacts. As the requirements are expressed in natural language, they can be an important source of defects. Aspects such as non ambiguity, completeness, and atomicity can be affected due the characteristics of natural language. Traditional practices focus on finding software bugs, as a corrective approach, until the project has been coded already, instead assuring quality since the beginning. By other hand, evaluating such quality attributes can be a difficult task. In this paper we propose some guidelines for a disciplined sentence structure for expressing the requirements, which allows natural language processing techniques to evaluate quality. We also propose a tool for automatic requirement evaluation based on the grammar structure of sentences expressed in natural language. With this tool we have a huge speed increase over manual evaluation. In order to validate our proposal we have implemented a set of experiments with real projects, assessing the impact of requirements quality over project results.