LEADER 00724nam0-22002651i-450- 001 990001141280403321 035 $a000114128 035 $aFED01000114128 035 $a(Aleph)000114128FED01 035 $a000114128 100 $a--------d--------km-y0itay50------ba 101 0 $aeng 200 1 $aCalculus of variations$fby Courant 210 $aNew York$cCourant Institute of Mathematical Sciences$d1945-46 610 0 $aCalcolo delle variazioni 700 1$aCourant,$bRichard$0331066 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990001141280403321 952 $a6-E-19$b7720$fMA1 959 $aMA1 962 $a49XX 996 $aCalculus of variations$9344132 997 $aUNINA DB $aING01 LEADER 01407nam 2200445 450 001 9910150309103321 005 20151212080942.0 010 $a1-62417-762-X 035 $a(CKB)3710000000942751 035 $a(MiAaPQ)EBC4745937 035 $a(EXLCZ)993710000000942751 100 $a20130529h20132013 uy| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 00$aNatural gas in the United States $estatus and opportunities /$fHector T. Murano, editor 210 1$aNew York :$cNova Science Publishers,$d[2013] 210 4$dİ2013 215 $a1 online resource (193 pages) $cillustrations 225 1 $aEnergy Science, Engineering and Technology 225 1 $aEnergy Policies, Politics and Prices 311 $a1-62417-761-1 320 $aIncludes bibliographical references and index. 410 0$aEnergy science, engineering and technology series. 410 0$aEnergy policies, politics and prices series. 606 $aNatural gas$zUnited States 606 $aGas industry$zUnited States 615 0$aNatural gas 615 0$aGas industry 676 $a338.2/72850973 702 $aMurano$b Hector T. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910150309103321 996 $aNatural gas in the United States$92877879 997 $aUNINA LEADER 03898nam 2200649 a 450 001 9910768173503321 005 20200520144314.0 010 $a3-540-45386-5 024 7 $a10.1007/11871743 035 $a(CKB)1000000000284049 035 $a(SSID)ssj0000320611 035 $a(PQKBManifestationID)11237920 035 $a(PQKBTitleCode)TC0000320611 035 $a(PQKBWorkID)10249708 035 $a(PQKB)11347145 035 $a(DE-He213)978-3-540-45386-4 035 $a(MiAaPQ)EBC3068141 035 $a(PPN)123138590 035 $a(EXLCZ)991000000000284049 100 $a20060822d2006 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aVariations on constants $eflow analysis of sequential and parallel programs /$fMarkus Muller-Olm 205 $a1st ed. 2006. 210 $aBerlin ;$aNew York $cSpringer$d2006 215 $a1 online resource (XIII, 177 p.) 225 1 $aLecture notes in computer science,$x0302-9743 ;$v3800 225 1 $aLNCS sublibrary. SL 2, Programming and software engineering 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-45385-7 320 $aIncludes bibliographical references. 327 $a1. Introduction -- 2. A Hierarchy of Constants -- 3. Deciding Constants by Effective Weakest Preconditions -- 4. Limits of Parallel Flow Analysis -- 5. Parallel Flow Graphs -- 6. Non-atomic Execution -- 7. Dependence Traces -- 8. Detecting Copy Constants and Eliminating Faint Code -- 9. Complexity in the Non-atomic Scenario -- 10. Conclusion -- A. A Primer on Constraint-Based Program Analysis. 330 $aProgram analysis is concerned with techniques that automatically determine run-time properties of given programs prior to run-time. It is used for validation in order to ensure that programs serve their intended purpose and in further processing for efficient execution such as in optimizing compilers. Optimal program analysis provides a guarantee about the precision of the computed results. This monograph, a revised version of the author's habilitation thesis, focusses on optimal flow analysis of sequential and parallel programs. It studies algorithmic properties of various versions of the well-known constant-propagation problem. In order to come to grips with the variants considered, it combines techniques from different areas such as linear algebra, computable ring theory, abstract interpretation, program verification, complexity theory, etc. Combination of techniques is the key to further progress in automatic analysis and constant-propagation allows us to illustrate this point in a theoretical study. After a general overview, the monograph consists of three essentially self-contained parts that can be read independently of each other. These parts study: a hierarchy of constants in sequential programs, inherent limits of flow analysis of parallel programs, and how to overcome these limits by abandoning a classic atomic execution assumption. 410 0$aLecture notes in computer science ;$v3800. 410 0$aLNCS sublibrary.$nSL 2,$pProgramming and software engineering. 606 $aParallel programming (Computer science) 606 $aSequential processing (Computer science) 606 $aMathematical constants 606 $aVariables (Mathematics) 606 $aComputer programs$xCorrectness 615 0$aParallel programming (Computer science) 615 0$aSequential processing (Computer science) 615 0$aMathematical constants. 615 0$aVariables (Mathematics) 615 0$aComputer programs$xCorrectness. 676 $a004.21 700 $aMuller-Olm$b Markus$0508822 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910768173503321 996 $aVariations on Constants$9772122 997 $aUNINA