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A Novel Checklist: Comparison of CBR and PBR to Inspect Use Case Specification

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Requirements Engineering in the Big Data Era

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 558))

Abstract

High quality and cost effective software development entails early detection of errors from requirement specification artifact/s. For this purpose, various inspection techniques have been presented to identify requirement specification errors. In most reported studies, comparison of two commonly used inspection techniques CBR (Checklist Based Reading) and PBR (Perspective Based Reading) had been conducted to identify defects from the UCS (Use Case Specification); however no comparison was done based on IEEE STD 830-1998 defects’ types. Therefore, a novel checklist was developed to identify the IEEE STD 830-1998 specified defects’ types namely Ambiguousness, Incorrectness, Inconsistency and Incompleteness from UCS, a major contribution of this research. This developed checklist was later validated to be utilized during this experimental research. In this study, a quasi-experiment was conducted with industrial professionals to compare the effectiveness and efficiency of CBR and PBR using the developed checklist to inspect the UCS that was specified in Use Case 2.0 format. The result of this research showed significant difference between CBR and PBR, i.e. PBR found more defects for all defects’ types compared to the CBR technique, but CBR reported less False Positive defects by applying the developed checklist for all defects’ types. It was also proved that CBR is more efficient (time based) than PBR for all defects’ types. These findings will provide guidelines to industry practitioners for the selection of an inspection technique based on effectiveness, efficiency and false positive ratio for a particular type of defect.

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Naveed, A., Ikram, N. (2015). A Novel Checklist: Comparison of CBR and PBR to Inspect Use Case Specification. In: Liu, L., Aoyama, M. (eds) Requirements Engineering in the Big Data Era. Communications in Computer and Information Science, vol 558. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-48634-4_8

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  • DOI: https://doi.org/10.1007/978-3-662-48634-4_8

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