Assisting requirement formalization by means of natural language translation
Formal Methods in System Design
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Processing natural language requirements
ASE '97 Proceedings of the 12th international conference on Automated software engineering (formerly: KBSE)
Processing Natural Language Software Requirement Specifications
ICRE '96 Proceedings of the 2nd International Conference on Requirements Engineering (ICRE '96)
Higher Quality Requirements Specifications through Natural Language Patterns
SWSTE '03 Proceedings of the IEEE International Conference on Software-Science, Technology & Engineering
Requirement Specification in Pseudo-Natural Language in PROMIS
COMPSAC '95 Proceedings of the 19th International Computer Software and Applications Conference
Monitoring and control in scenario-based requirements analysis
Proceedings of the 27th international conference on Software engineering
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
On Formalism in Specifications
IEEE Software
Information and Software Technology
An empirically-based process to improve the practice of requirement review
ICSP'08 Proceedings of the Software process, 2008 international conference on Making globally distributed software development a success story
On specifying requirements using a semantically controlled representation
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Mining textual requirements to assist architectural software design: a state of the art review
Artificial Intelligence Review
Hi-index | 0.00 |
Requirements Engineering (RE) is concerned with the gathering, analyzing, specifying and validating of user requirements that are documented mostly in natural language. The artifact produced by the RE process is the software requirements specification (SRS) document. The success of a software project largely depends on the quality of SRS documentation, which serves as an input to the design, coding and testing phases. This paper approaches the problem of the automatic quality assessment of textual requirements from an innovative point of view, namely the use of the Natural Language Processing (NLP) text classification technique. The paper proposes a quality model for the requirements text and a text classification system to automate the quality assessment process. A large study evaluating the discriminatory power of the quality characteristics and the feasibility of a tool for the automatic detection of ambiguities in requirements documentation is presented. The study also provides a benchmark for such an evaluation and an upper bound on what we can expect automatic requirements quality assessment tools to achieve. The reported research is part of a larger project on the applicability of NLP techniques to assess the quality of artifacts produced in RE.