{"id":"https://openalex.org/W3158709324","doi":"https://doi.org/10.1109/ispass51385.2021.00032","title":"Comparative Code Structure Analysis using Deep Learning for Performance Prediction","display_name":"Comparative Code Structure Analysis using Deep Learning for Performance Prediction","publication_year":2021,"publication_date":"2021-03-01","ids":{"openalex":"https://openalex.org/W3158709324","doi":"https://doi.org/10.1109/ispass51385.2021.00032","mag":"3158709324"},"language":"en","primary_location":{"id":"doi:10.1109/ispass51385.2021.00032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispass51385.2021.00032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","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/A5058282095","display_name":"Tarek Ramadan","orcid":"https://orcid.org/0000-0002-6489-7668"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Tarek Ramadan","raw_affiliation_strings":["Texas State University"],"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002465410","display_name":"Tanzima Islam","orcid":"https://orcid.org/0000-0003-2877-5871"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tanzima Z. Islam","raw_affiliation_strings":["Texas State University"],"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005889420","display_name":"Chase Phelps","orcid":"https://orcid.org/0000-0003-1480-0917"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chase Phelps","raw_affiliation_strings":["Texas State University"],"affiliations":[{"raw_affiliation_string":"Texas State University","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011916862","display_name":"Nathan Pinnow","orcid":null},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nathan Pinnow","raw_affiliation_strings":["Lawrence Livermore National Laboratory"],"affiliations":[{"raw_affiliation_string":"Lawrence Livermore National Laboratory","institution_ids":["https://openalex.org/I1282311441"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046632395","display_name":"Jayaraman J. Thiagarajan","orcid":"https://orcid.org/0000-0002-8517-5816"},"institutions":[{"id":"https://openalex.org/I1282311441","display_name":"Lawrence Livermore National Laboratory","ror":"https://ror.org/041nk4h53","country_code":"US","type":"facility","lineage":["https://openalex.org/I1282311441","https://openalex.org/I1330989302","https://openalex.org/I198811213","https://openalex.org/I4210138311"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jayaraman J. Thiagarajan","raw_affiliation_strings":["Lawrence Livermore National Laboratory"],"affiliations":[{"raw_affiliation_string":"Lawrence Livermore National Laboratory","institution_ids":["https://openalex.org/I1282311441"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5058282095"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.3049,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.92865545,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"151","last_page":"161"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10260","display_name":"Software Engineering Research","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12127","display_name":"Software System Performance and Reliability","score":0.9993000030517578,"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"}},{"id":"https://openalex.org/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.977400004863739,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8746668100357056},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.6808597445487976},{"id":"https://openalex.org/keywords/abstract-syntax-tree","display_name":"Abstract syntax tree","score":0.6701905727386475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6468683481216431},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5656181573867798},{"id":"https://openalex.org/keywords/correctness","display_name":"Correctness","score":0.564781665802002},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5644065737724304},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5596064329147339},{"id":"https://openalex.org/keywords/abstract-syntax","display_name":"Abstract syntax","score":0.5008668899536133},{"id":"https://openalex.org/keywords/code","display_name":"Code (set theory)","score":0.4856894910335541},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.439347505569458},{"id":"https://openalex.org/keywords/syntax","display_name":"Syntax","score":0.3917997181415558},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34153252840042114},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.2711789608001709}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8746668100357056},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.6808597445487976},{"id":"https://openalex.org/C58646249","wikidata":"https://www.wikidata.org/wiki/Q127380","display_name":"Abstract syntax tree","level":3,"score":0.6701905727386475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6468683481216431},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5656181573867798},{"id":"https://openalex.org/C55439883","wikidata":"https://www.wikidata.org/wiki/Q360812","display_name":"Correctness","level":2,"score":0.564781665802002},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5644065737724304},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5596064329147339},{"id":"https://openalex.org/C114408938","wikidata":"https://www.wikidata.org/wiki/Q333373","display_name":"Abstract syntax","level":3,"score":0.5008668899536133},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.4856894910335541},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.439347505569458},{"id":"https://openalex.org/C60048249","wikidata":"https://www.wikidata.org/wiki/Q37437","display_name":"Syntax","level":2,"score":0.3917997181415558},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34153252840042114},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.2711789608001709},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ispass51385.2021.00032","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ispass51385.2021.00032","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1485912969","https://openalex.org/W1512847993","https://openalex.org/W1614298861","https://openalex.org/W1815076433","https://openalex.org/W1979360936","https://openalex.org/W2016589492","https://openalex.org/W2026212799","https://openalex.org/W2079735306","https://openalex.org/W2120615054","https://openalex.org/W2124292065","https://openalex.org/W2142403498","https://openalex.org/W2146957318","https://openalex.org/W2154851992","https://openalex.org/W2187089797","https://openalex.org/W2250539671","https://openalex.org/W2402268235","https://openalex.org/W2519887557","https://openalex.org/W2548523184","https://openalex.org/W2604314403","https://openalex.org/W2618564128","https://openalex.org/W2742956140","https://openalex.org/W2786676889","https://openalex.org/W2896903901","https://openalex.org/W2911286998","https://openalex.org/W2949676527","https://openalex.org/W2950577311","https://openalex.org/W2963355447","https://openalex.org/W2963661253","https://openalex.org/W2964015378","https://openalex.org/W2964132723","https://openalex.org/W2979271470","https://openalex.org/W2999343753","https://openalex.org/W3104097132","https://openalex.org/W3146720657","https://openalex.org/W6630611416","https://openalex.org/W6638545294","https://openalex.org/W6713098461","https://openalex.org/W6729030020","https://openalex.org/W6763902437","https://openalex.org/W6948116018"],"related_works":["https://openalex.org/W2077104824","https://openalex.org/W2536864162","https://openalex.org/W2613250302","https://openalex.org/W2095633838","https://openalex.org/W2390421503","https://openalex.org/W3184653409","https://openalex.org/W1988370859","https://openalex.org/W2185876338","https://openalex.org/W2387926336","https://openalex.org/W319507398"],"abstract_inverted_index":{"Performance":[0],"analysis":[1,26,107],"has":[2],"always":[3],"been":[4],"an":[5],"afterthought":[6],"during":[7],"the":[8,21,37,55,61,101,123,128,134,141,157,178,194,201,206,209,275],"application":[9,14,43,188,195],"development":[10,189],"process,":[11],"focusing":[12],"on":[13,177],"correctness":[15],"first.":[16],"The":[17],"learning":[18,74,132,217],"curve":[19],"of":[20,48,51,88,96,122,130,144,159,170,193,208,254,274],"existing":[22],"static":[23,162],"and":[24,58,63,103,251,272],"dynamic":[25],"tools":[27],"are":[28],"steep,":[29],"which":[30,203],"requires":[31],"understanding":[32],"low-level":[33],"details":[34],"to":[35,69,109,133,148,155,172,198,200,238,270],"interpret":[36],"findings":[38],"for":[39,100,136,219],"actionable":[40],"optimizations.":[41],"Additionally,":[42],"performance":[44,174,207],"is":[45],"a":[46,49,78,93,97,105,248,252,261],"function":[47],"number":[50],"unknowns":[52,112],"stemming":[53],"from":[54,140],"application-,":[56],"runtime-,":[57],"interactions":[59],"between":[60,118],"OS":[62],"underlying":[64],"hardware,":[65],"making":[66],"it":[67],"difficult":[68],"model":[70],"using":[71,160,247],"any":[72],"deep":[73,131,214],"technique,":[75],"especially":[76],"without":[77],"large":[79,94],"labeled":[80,98],"dataset.":[81],"In":[82],"this":[83],"paper,":[84],"we":[85],"address":[86],"both":[87],"these":[89],"problems":[90,256],"by":[91],"presenting":[92],"corpus":[95],"dataset":[99],"community":[102],"take":[104],"comparative":[106],"approach":[108],"mitigate":[110],"all":[111],"except":[113],"their":[114],"source":[115,150,220,234,262],"code":[116,181,263],"differences":[117],"different":[119],"correct":[120],"implementations":[121],"same":[124],"problem.":[125],"We":[126,211],"put":[127],"power":[129],"test":[135],"automatically":[137],"extracting":[138],"information":[139,163],"hierarchical":[142,236],"structure":[143,237],"abstract":[145,165],"syntax":[146,166],"trees":[147],"represent":[149],"code.":[151,221],"This":[152,183],"paper":[153],"aims":[154],"assess":[156],"feasibility":[158],"purely":[161],"(e.g.,":[164],"tree":[167],"or":[168,267],"AST)":[169],"applications":[171],"predict":[173,259],"change":[175,179],"based":[176],"in":[180],"structure.":[182],"research":[184],"will":[185,196,204,264],"enable":[186],"performance-aware":[187],"since":[190],"every":[191],"version":[192],"continue":[197],"contribute":[199],"corpora,":[202],"enhance":[205],"model.":[210],"evaluate":[212],"several":[213],"learning-based":[215],"representation":[216],"techniques":[218],"Our":[222],"results":[223],"show":[224],"that":[225],"tree-based":[226],"Long":[227],"Short-Term":[228],"Memory":[229],"(LSTM)":[230],"models":[231,245],"can":[232,257],"leverage":[233],"code's":[235],"discover":[239],"latent":[240],"representations.":[241],"Specifically,":[242],"LSTM-based":[243],"predictive":[244],"built":[246],"single":[249],"problem":[250],"combination":[253],"multiple":[255],"correctly":[258],"if":[260],"perform":[265],"better":[266],"worse":[268],"up":[269],"84%":[271],"73%":[273],"time,":[276],"respectively.":[277]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
