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Defect Localization using Dynamic Call Tree Mining and Matching and Request Replication: An Alternative to QoS-aware Service Selection

<p>This thesis is concerned with two separate subjects; (i) Defect localization using tree mining and tree matching, and (ii) Quality-of-service-aware service selection; it is divided into these parts accordingly.</p> / <p>This thesis is concerned with two separate subjects; (i) Defect localization using tree mining and tree matching, and (ii) Quality-of-service-aware service selection; it is divided into these parts accordingly.</p> <p>In the first part of this thesis we present a novel technique for defect localization which is able to localize call-graph-affecting defects using tree mining and tree matching techniques. In this approach, given a set of successful executions and a failing execution and by following a series of analyses we generate an extended report of suspicious method calls. The proposed defect localization technique is implemented as a prototype and evaluated using four subject programs of various sizes, developed in Java or C. Our experiments show comparable results to similar defect localization tools, but unlike most of its counterparts, we do not require the availability of multiple failing executions to localize the defects. We believe that this is a major advantage, since it is often the case that we have only a single failing execution to work with. Potential risks of the proposed technique are also investigated.</p> <p>In the second part of this thesis we present an alternative strategy for service selection in service oriented architecture, which provides better quality services for less cost. The proposed Request Replication technique replicates a client’s request over a number of cheap, low quality services to gain the required quality of service. Following this approach, we also present a number of recommendations about how service providers should advertise non-functional properties of their services.</p> / Doctor of Philosophy (PhD)

Identiferoai:union.ndltd.org:mcmaster.ca/oai:macsphere.mcmaster.ca:11375/13753
Date04 1900
CreatorsYousefi, Anis
ContributorsWassyng, Alan, Down, Douglas G., Computing and Software
Source SetsMcMaster University
Detected LanguageEnglish
Typethesis

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