Ionic: Collaborating causal fault localization

Resource type
Thesis type
(Thesis) M.Sc.
Date created
2019-09-23
Authors/Contributors
Abstract
Fault localization techniques-FLTs assist in efficient localization of faults in software programs. However, conventional FLTs such as heuristic-based Spectrum Based Fault Localization are mainly investigated on the individual statement granularity. At statement granularity, elements are considered in isolation. Hence, the information flow between them is ignored. This creates unfavourable circumstances when localizing defects with multiple collaborating faulty program elements. This thesis presents Ionic, an extension to an existing statement level FLT that incorporates information about how statements may collaborate to cause a bug. Ionic leverages the construction of causal models for collections of statements with respect to a bug. Ionic is then used within a new FLT, Hera, to efficiently localize bugs including multiple collaborating statements. Experimental results on real world software defects in the Defects4J benchmark suite show that Hera is better at localizing defects with multiple collaborating faulty elements.
Document
Identifier
etd20554
Copyright statement
Copyright is held by the author.
Permissions
This thesis may be printed or downloaded for non-commercial research and scholarly purposes.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Sumner, Nick
Member of collection
Attachment Size
etd20554.pdf 1.08 MB