NOISE DETECTION IN SOFTWARE REQUIREMENTS SPECIFICATION DOCUMENT USING SPECTRAL CLUSTERING

Abstract

Requirements engineering phase in software development resulting in a SRS (Software Requirements Specification) document. The use of natural language approach in generating such document has some drawbacks that caused 7 common mistakes among the engineer which had been formulated by Meyer as "The 7 sins of specifier". One of the 7 common mistakes is noise. This study attempted to detect noise in software requirements with spectral clustering. The clustering algorithm working on fewer dimensions compared to others. The resulting kappa coefficient is 0.4426 . The result showed that the consistency between noise prediction and noise assessment made by three annotators is still low.