000 | 03965nam a22005895i 4500 | ||
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001 | 978-3-540-36614-0 | ||
003 | DE-He213 | ||
005 | 20240423132525.0 | ||
007 | cr nn 008mamaa | ||
008 | 121227s2003 gw | s |||| 0|eng d | ||
020 |
_a9783540366140 _9978-3-540-36614-0 |
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024 | 7 |
_a10.1007/3-540-36614-8 _2doi |
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050 | 4 | _aQA76.758 | |
072 | 7 |
_aUMZ _2bicssc |
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072 | 7 |
_aCOM051230 _2bisacsh |
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072 | 7 |
_aUMZ _2thema |
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082 | 0 | 4 |
_a005.1 _223 |
100 | 1 |
_aFahringer, Thomas. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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245 | 1 | 0 |
_aAdvanced Symbolic Analysis for Compilers _h[electronic resource] : _bNew Techniques and Algorithms for Symbolic Program Analysis and Optimization / _cby Thomas Fahringer, Bernhard Scholz. |
250 | _a1st ed. 2003. | ||
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2003. |
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300 |
_aXII, 136 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2628 |
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505 | 0 | _aSymbolic Analysis of Programs -- Generating Program Contexts -- Symbolic Analysis Algorithms and Transformations -- Symbolic Analysis for Parallelizing Compilers -- Related Work -- Conclusion. | |
520 | _aThe objective of program analysis is to automatically determine the p- perties of a program. Tools of software development, such as compilers, p- formance estimators, debuggers, reverse-engineering tools, program veri?- tion/testing/proving systems, program comprehension systems, and program specializationtoolsarelargelydependentonprogramanalysis. Advancedp- gram analysis can: help to ?nd program errors; detect and tune performan- critical code regions; ensure assumed constraints on data are not violated; tailor a generic program to suit a speci?c application; reverse-engineer so- ware modules, etc. A prominent program analysis technique is symbolic a- lysis, which has attracted substantial attention for many years as it is not dependent on executing a program to examine the semantics of a program, and it can yield very elegant formulations of many analyses. Moreover, the complexity of symbolic analysis can be largely independent of the input data size of a program and of the size of the machine on which the program is being executed. In this book we present novel symbolic control and data ?ow repres- tation techniques as well as symbolic techniques and algorithms to analyze and optimize programs. Program contexts which de?ne a new symbolic - scription of program semantics for control and data ?ow analysis are at the center of our approach. We have solved a number of problems encountered in program analysis by using program contexts. Our solution methods are e?cient, versatile, uni?ed, and more general (they cope with regular and irregular codes) than most existing methods. | ||
650 | 0 | _aSoftware engineering. | |
650 | 0 | _aCompilers (Computer programs). | |
650 | 0 | _aOperating systems (Computers). | |
650 | 0 | _aComputer science. | |
650 | 1 | 4 | _aSoftware Engineering. |
650 | 2 | 4 | _aCompilers and Interpreters. |
650 | 2 | 4 | _aOperating Systems. |
650 | 2 | 4 | _aComputer Science Logic and Foundations of Programming. |
700 | 1 |
_aScholz, Bernhard. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783540011859 |
776 | 0 | 8 |
_iPrinted edition: _z9783662205839 |
830 | 0 |
_aLecture Notes in Computer Science, _x1611-3349 ; _v2628 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/3-540-36614-8 |
912 | _aZDB-2-SCS | ||
912 | _aZDB-2-SXCS | ||
912 | _aZDB-2-LNC | ||
912 | _aZDB-2-BAE | ||
942 | _cSPRINGER | ||
999 |
_c188702 _d188702 |