AUTOMATIC CRITICAL SECTION DISCOVERY USING MEMORY USAGE PATTERNS.

Simple item page
dc.contributor.advisorYeung, Donalden_US
dc.contributor.authorStechschulte, Lisa Marieen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2012-07-10T05:40:57Z
dc.date.available2012-07-10T05:40:57Z
dc.date.issued2012en_US
dc.description.abstractParallel programming introduces new types of bugs that are notoriously difficult to find. As a result researchers have put a significant amount of effort into creating tools and techniques to discover parallel bugs. One of these bugs is the violation of the assumption of <bold>atomicity</bold>-- the assumption that a region of code, called a <bold>critical section</bold>, executes without interruption from an outside operation. In this thesis, we introduce a new heuristic to infer critical sections using the temporal and spatial locality of critical sections and provide empirical results showing that the heuristic can infer critical sections in shared memory programs. Real critical sections in benchmark programs are completely covered by inferred critical sections up to 75% to 80% of the time. A programmer can use the reported critical sections to inform his addition of locks into the program.en_US
dc.identifier.urihttp://hdl.handle.net/1903/12820
dc.subject.pqcontrolledComputer engineeringen_US
dc.subject.pqcontrolledComputer scienceen_US
dc.subject.pqcontrolledElectrical engineeringen_US
dc.subject.pquncontrolledAtomicityen_US
dc.subject.pquncontrolledCritical Sectionen_US
dc.subject.pquncontrolledMemoryen_US
dc.titleAUTOMATIC CRITICAL SECTION DISCOVERY USING MEMORY USAGE PATTERNS.en_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Stechschulte_umd_0117N_13240.pdf
Size:
2.57 MB
Format:
Adobe Portable Document Format
Download

Collections

UMD Theses and Dissertations
Electrical & Computer Engineering Theses and Dissertations