{"id":"https://openalex.org/W4229530432","doi":"https://doi.org/10.1109/pact.2003.1238012","title":"Compressing extended program traces using value predictors","display_name":"Compressing extended program traces using value predictors","publication_year":2004,"publication_date":"2004-03-22","ids":{"openalex":"https://openalex.org/W4229530432","doi":"https://doi.org/10.1109/pact.2003.1238012"},"language":"en","primary_location":{"id":"doi:10.1109/pact.2003.1238012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pact.2003.1238012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Oceans 2002 Conference and Exhibition. Conference Proceedings (Cat. No.02CH37362)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103125276","display_name":"Martin Burtscher","orcid":"https://orcid.org/0000-0001-7717-3354"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"M. Burtscher","raw_affiliation_strings":["Computer Systems Laboratory, Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Computer Systems Laboratory, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064869477","display_name":"Metha Jeeradit","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Metha Jeeradit","raw_affiliation_strings":["Computer Systems Laboratory, Cornell University, Ithaca, NY, USA"],"affiliations":[{"raw_affiliation_string":"Computer Systems Laboratory, Cornell University, Ithaca, NY, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103125276"],"corresponding_institution_ids":["https://openalex.org/I205783295"],"apc_list":null,"apc_paid":null,"fwci":2.8963,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.90760799,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"17","issue":null,"first_page":"159","last_page":"169"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1708","display_name":"Hardware and Architecture"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11269","display_name":"Algorithms and Data Compression","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11181","display_name":"Advanced Data Storage Technologies","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.8799935579299927},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8370429873466492},{"id":"https://openalex.org/keywords/compression","display_name":"Compression (physics)","score":0.6873214244842529},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.6589948534965515},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.6552735567092896},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5382364392280579},{"id":"https://openalex.org/keywords/data-compression-ratio","display_name":"Data compression ratio","score":0.4859522581100464},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4582172930240631},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.4476895034313202},{"id":"https://openalex.org/keywords/computer-engineering","display_name":"Computer engineering","score":0.4133650064468384},{"id":"https://openalex.org/keywords/parallel-computing","display_name":"Parallel computing","score":0.365200400352478},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.1949721872806549},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.10781940817832947},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.07892706990242004}],"concepts":[{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.8799935579299927},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8370429873466492},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.6873214244842529},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.6589948534965515},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6552735567092896},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5382364392280579},{"id":"https://openalex.org/C94835093","wikidata":"https://www.wikidata.org/wiki/Q3113333","display_name":"Data compression ratio","level":5,"score":0.4859522581100464},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4582172930240631},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.4476895034313202},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.4133650064468384},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.365200400352478},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.1949721872806549},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.10781940817832947},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.07892706990242004},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/pact.2003.1238012","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pact.2003.1238012","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Oceans 2002 Conference and Exhibition. Conference Proceedings (Cat. No.02CH37362)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1480780803","https://openalex.org/W1489781149","https://openalex.org/W1987238172","https://openalex.org/W1988637082","https://openalex.org/W1990653637","https://openalex.org/W2045113359","https://openalex.org/W2047226031","https://openalex.org/W2059504991","https://openalex.org/W2085880494","https://openalex.org/W2087501426","https://openalex.org/W2095872092","https://openalex.org/W2096458542","https://openalex.org/W2105686649","https://openalex.org/W2107745473","https://openalex.org/W2108112890","https://openalex.org/W2129652681","https://openalex.org/W2130182357","https://openalex.org/W2132292826","https://openalex.org/W2133304975","https://openalex.org/W2138026948","https://openalex.org/W2145561364","https://openalex.org/W2145607884","https://openalex.org/W2146210875","https://openalex.org/W2159617380","https://openalex.org/W4233531165","https://openalex.org/W4237526698","https://openalex.org/W4247080994","https://openalex.org/W4249018157","https://openalex.org/W4250927075","https://openalex.org/W4253048710","https://openalex.org/W4253172818","https://openalex.org/W6629170583","https://openalex.org/W6681485427"],"related_works":["https://openalex.org/W2207317090","https://openalex.org/W624280404","https://openalex.org/W2088378984","https://openalex.org/W3008492011","https://openalex.org/W2169853506","https://openalex.org/W3080614128","https://openalex.org/W2393930276","https://openalex.org/W2385628723","https://openalex.org/W3035703949","https://openalex.org/W2356487475"],"abstract_inverted_index":{"Trace":[0],"files":[1],"record":[2],"the":[3,35,38,87,117],"execution":[4],"behavior":[5],"of":[6,37,111,119],"programs":[7],"for":[8,30],"future":[9],"analysis.":[10],"Unfortunately,":[11],"nontrivial":[12],"program":[13,135],"traces":[14,31,48,67,102],"tend":[15],"to":[16,22,69,86,113,131],"be":[17,23,44,129],"very":[18],"large":[19],"and":[20,73,76,100,123],"have":[21],"compressed.":[24],"While":[25],"good":[26],"compression":[27,89,109,121],"schemes":[28,42],"exist":[29],"that":[32,49],"capture":[33],"only":[34],"PCs":[36],"executed":[39],"instructions,":[40],"these":[41],"can":[43,128],"ineffective":[45],"on":[46,82],"extended":[47,66,134],"include":[50],"important":[51],"additional":[52],"information":[53],"such":[54],"as":[55,80],"register":[56],"values":[57],"or":[58],"effective":[59],"addresses.":[60],"Our":[61],"novel,":[62],"value-prediction-based":[63],"approach":[64],"compresses":[65,101],"up":[68,112],"22.8":[70],"times":[71,79],"better":[72],"about":[74],"two":[75],"a":[77,96],"half":[78],"well":[81],"average.":[83],"In":[84],"addition":[85],"higher":[88],"rate,":[90],"our":[91,120],"lossless":[92],"single-pass":[93],"algorithm":[94],"has":[95],"fixed":[97],"memory":[98],"requirement":[99],"faster":[103],"than":[104],"other":[105],"algorithms.":[106],"It":[107],"achieves":[108],"rates":[110],"6170.":[114],"We":[115],"describe":[116],"design":[118],"method":[122],"illustrate":[124],"how":[125],"value":[126],"predictors":[127],"used":[130],"effectively":[132],"compress":[133],"traces.":[136]},"counts_by_year":[{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}