A Framework to Predict Software “Quality in Use” from Software Reviews
Software reviews are verified to be a good source of users’ experience. The software “quality in use” concerns meeting users’ needs. Current software quality models such as McCall and Boehm, are built to support software development process, rather than users perspectives. In this paper, opinion mining is used to extract and summarize software “quality in use” from software reviews. A framework to detect software “quality in use” as defined by the ISO/IEC 25010 standard is presented here. The framework employs opinion-feature double propagation to expand predefined lists of software “quality in use” features to domain specific features. Clustering is used to learn software feature “quality in use” characteristics group. A preliminary result of extracted software features shows promising results in this direction.
Keywords“Quality in use” Software reviews Opinion mining ISO 25010 Quality model Product reviews
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This study was supported in part by Universiti Malaysia Sarawak’ Zamalah Graduate Scholarship and grant from ERGS/ICT07(01)/1018/2013(15).
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