SMArTIC: Specification Mining Architecture with Trace fIltering and Clustering

dc.contributor.authorLO, Daviden_US
dc.contributor.authorKHOO, Siau-Chengen_US
dc.date.accessioned2006-09-07T04:27:11Zen_US
dc.date.accessioned2017-01-23T06:59:56Z
dc.date.available2006-09-07T04:27:11Zen_US
dc.date.available2017-01-23T06:59:56Z
dc.date.issued2006-08-31en_US
dc.description.abstractImproper management of software evolution, compounded by imprecise, and changing requirements and short time to market requirement, commonly leads to a lack of up-to-date specification. This can result in software that is characterized by presence of bugs, anomalies and even security threats. Software specification mining is a new technique to address this concern by inferring specifications automatically. In this paper, we propose a novel API specification mining architecture called SMArTIC (Specification Mining Architecture with Trace fIltering and Clustering) to improve the accuracy, robustness and scalability of specification miners. This architecture is constructed based on two hypotheses: (1) Erroneous transactions should be pruned from traces input to a miner, and (2) Clustering related traces will localize inaccuracies in learning and reduce over-generalization. Corresponding, SMArTIC comprises four components: an erroneous-trace filtering block, a related-trace clustering block, a learner, and a merger. We show through experiment that the quality of specification miner can be significantly improved using SMArTIC.en_US
dc.format.extent675515 bytesen_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.urihttps://dl.comp.nus.edu.sg/xmlui/handle/1900.100/2246en_US
dc.language.isoenen_US
dc.relation.ispartofseriesTRA8/06en_US
dc.titleSMArTIC: Specification Mining Architecture with Trace fIltering and Clusteringen_US
dc.typeTechnical Reporten_US
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