Abstract
AbstractSoftware Requirements Specifications (SRS) documents are important artifacts in the software industry. A SRS contains all the requirements specifications for a software system, either as functional requirements (FR) or non-functional requirements (NFR). FRs are the features of the system-to-be, whereas NFRs define its quality attributes. NFRs impact the system as a whole and interact both with each other and with the functional requirements. SRS documents are typically written in informal natural language [1], which impedes their automated analysis. The goal of this work is to support software engineers with semantic analysis methods that can automatically extract and analyze requirements written in natural language texts, in order to (i) make SRS documents machine-processable by transforming them into an ontological representation; (ii) apply quality assurance (QA) methods on the extracted requirements, in order to detect defects, like ambiguities or omissions; and (iii) attempt to build traceability links between NFRs and the FRs impacted by them, in order to aid effort estimation models.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
