Predicting program execution times by analyzing static and dynamic program paths
dc.contributor.author | Park, Chang Yun | en_US |
dc.date.accessioned | 2006-09-11T19:44:58Z | |
dc.date.available | 2006-09-11T19:44:58Z | |
dc.date.issued | 1993-03 | en_US |
dc.identifier.citation | Park, Chang Yun; (1993). "Predicting program execution times by analyzing static and dynamic program paths." Real-Time Systems 5(1): 31-62. <http://hdl.handle.net/2027.42/48084> | en_US |
dc.identifier.issn | 0922-6443 | en_US |
dc.identifier.issn | 1573-1383 | en_US |
dc.identifier.uri | https://hdl.handle.net/2027.42/48084 | |
dc.description.abstract | This paper describes a method to predict guaranteed and tight deterministic execution time bounds of a sequential program. The basic prediction technique is a static analysis based on simple timing schema for source-level language constructs, which gives accurate predictions in many cases. Using powerful user-provided information, dynamic path analysis refines looser predictions by eliminating infeasible paths and decomposing the possible execution behaviors in a pathwise manner. Overall prediction cost is scalable with respect to desired precision, controlling the amount of information provided. We introduce a formal path model for dynamic path analysis, where user execution information is represented by a set of program paths. With a well-defined practical high-level interface language, user information can be used in an easy and efficient way. We also introduce a method to verify given user information with known program verification techniques. Initial experiments with a timing tool show that safe and tight predictions are possible for a wide range of programs. The tool can also provide predictions for interesting subsets of program executions. | en_US |
dc.format.extent | 2322790 bytes | |
dc.format.extent | 3115 bytes | |
dc.format.mimetype | application/pdf | |
dc.format.mimetype | text/plain | |
dc.language.iso | en_US | |
dc.publisher | Kluwer Academic Publishers; Springer Science+Business Media | en_US |
dc.subject.other | Computer Science | en_US |
dc.subject.other | Performance and Reliability | en_US |
dc.subject.other | Processor Architectures | en_US |
dc.subject.other | Special Purpose and Application-Based Systems | en_US |
dc.subject.other | System Performance and Evaluation | en_US |
dc.subject.other | Communications Engineering, Networks | en_US |
dc.subject.other | Control Engineering | en_US |
dc.title | Predicting program execution times by analyzing static and dynamic program paths | en_US |
dc.type | Article | en_US |
dc.subject.hlbsecondlevel | Management | en_US |
dc.subject.hlbsecondlevel | Business (General) | en_US |
dc.subject.hlbsecondlevel | Computer Science | en_US |
dc.subject.hlbsecondlevel | Economics | en_US |
dc.subject.hlbtoplevel | Engineering | en_US |
dc.subject.hlbtoplevel | Business | en_US |
dc.description.peerreviewed | Peer Reviewed | en_US |
dc.contributor.affiliationum | Department of Computer Science and Engineering, FR-35, University of Washington, 98195, Seattle, WA; EECS Department, University of Michigan, 48109, Ann Arbor, MI | en_US |
dc.contributor.affiliationumcampus | Ann Arbor | en_US |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/48084/1/11241_2005_Article_BF01088696.pdf | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/BF01088696 | en_US |
dc.identifier.source | Real-Time Systems | en_US |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
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