LEADER 04299nam 22007455 450 001 996465870803316 005 20200702003338.0 010 $a1-280-86572-5 010 $a9786610865727 010 $a3-540-71878-8 024 7 $a10.1007/978-3-540-71878-9 035 $a(CKB)1000000000284077 035 $a(EBL)3036632 035 $a(SSID)ssj0000292741 035 $a(PQKBManifestationID)11213251 035 $a(PQKBTitleCode)TC0000292741 035 $a(PQKBWorkID)10269773 035 $a(PQKB)11396590 035 $a(DE-He213)978-3-540-71878-9 035 $a(MiAaPQ)EBC3036632 035 $a(MiAaPQ)EBC6284383 035 $a(PPN)123161665 035 $a(EXLCZ)991000000000284077 100 $a20100301d2007 u| 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aCooperative Bug Isolation$b[electronic resource] $eWinning Thesis of the 2005 ACM Doctoral Dissertation Competition /$fby Ben Liblit 205 $a1st ed. 2007. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2007. 215 $a1 online resource (112 p.) 225 1 $aProgramming and Software Engineering ;$v4440 300 $aRevised version of the author's thesis (Ph.D.)--University of California, Berkeley, 2004. 300 $a"Association for Computing Machinery"--Cover. 311 $a3-540-71877-X 320 $aIncludes bibliographical references (pages [97]-101) and index. 327 $aInstrumentation Framework -- Practical Considerations -- Techniques for Statistical Debugging -- Related Work -- Conclusion. 330 $aEfforts to understand and predict the behavior of software date back to the earliest days of computer programming,over half a century ago. In the intervening decades, the need for effective methods of understanding software has only increased; so- ware has spread to become the underpinning of much of modern society, and the potentially disastrous consequences of broken or poorly understood software have become all too apparent. Ben Liblit?s work reconsiders two common assumptions about how we should analyze software and it arrives at some striking new results. Inprinciple,understandingsoftware is not such a hardproblem. Certainlya c- puter scientist studying programs appears to be in a much stronger position than, say, a biologist trying to understand a living organism or an economist trying to understand the behavior of markets, because the biologist and the economist must rely on indirect observation of the basic processes they wish to understand. A c- puterscientist, however,starts with a complete,precise descriptionof the behaviorof software?the program itself! Of course, the story turns out not to be so straightf- ward, because despite having a perfect description, programs are suf ciently c- plex that it is usually dif cult or even impossible to answer many simple questions about them. 410 0$aProgramming and Software Engineering ;$v4440 606 $aSoftware engineering 606 $aComputer logic 606 $aAlgorithms 606 $aSoftware Engineering/Programming and Operating Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/I14002 606 $aSoftware Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/I14029 606 $aLogics and Meanings of Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/I1603X 606 $aAlgorithm Analysis and Problem Complexity$3https://scigraph.springernature.com/ontologies/product-market-codes/I16021 615 0$aSoftware engineering. 615 0$aComputer logic. 615 0$aAlgorithms. 615 14$aSoftware Engineering/Programming and Operating Systems. 615 24$aSoftware Engineering. 615 24$aLogics and Meanings of Programs. 615 24$aAlgorithm Analysis and Problem Complexity. 676 $a005.1068 700 $aLiblit$b Ben$4aut$4http://id.loc.gov/vocabulary/relators/aut$0508805 712 02$aAssociation for Computing Machinery. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996465870803316 996 $aCooperative Bug Isolation$9772424 997 $aUNISA