Title:
Software Behavior: Automatic Classification and its Applications

dc.contributor.author Bowring, James Frederick
dc.contributor.author Rehg, James M.
dc.contributor.author Harrold, Mary Jean
dc.date.accessioned 2005-03-28T15:07:59Z
dc.date.available 2005-03-28T15:07:59Z
dc.date.issued 2003
dc.description.abstract A program's behavior is ultimately the collection of all its executions. This collection is diverse, unpredictable, and generally unbounded. Thus it is especially suited to statistical analysis and machine learning techniques. We explore the thesis that 1st- and 2nd-order Markov models of event-transitions are effective predictors of program behavior. We present a technique that models program executions as Markov models, and a clustering method for Markov models that aggregates multiple program executions, yielding a statistical description of program behaviors. With this approach, we can train classifiers to recognize specific behaviors emitted by an execution without knowledge of inputs or outcomes. We evaluate an application of active learning to the efficient refinement of our classifiers by conducting three empirical studies that explore a scenario illustrating automated test plan augmentation. We present a set of potential research questions and applications that our work suggests. en
dc.format.extent 453796 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/5937
dc.language.iso en_US
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries CERCS;GIT-CERCS-03-19
dc.subject Classification techniques en
dc.subject Data clustering en
dc.subject Empirical studies en
dc.subject Event-transitions en
dc.subject Machine learning en
dc.subject Markov models en
dc.subject Modeling en
dc.subject Predictors en
dc.subject Program behavior en
dc.subject Program executions en
dc.subject Statistical analysis en
dc.subject Statistical description of program behaviors
dc.title Software Behavior: Automatic Classification and its Applications en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.author Harrold, Mary Jean
local.contributor.author Rehg, James M.
local.contributor.corporatename Center for Experimental Research in Computer Systems
local.relation.ispartofseries CERCS Technical Report Series
relation.isAuthorOfPublication a81ec5a9-452c-4407-a97d-77364fcc8af2
relation.isAuthorOfPublication af5b46ec-ffe2-4ce4-8722-1373c9b74a37
relation.isOrgUnitOfPublication 1dd858c0-be27-47fd-873d-208407cf0794
relation.isSeriesOfPublication bc21f6b3-4b86-4b92-8b66-d65d59e12c54
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