{"id":"https://openalex.org/W4312354494","doi":"https://doi.org/10.1145/3524610.3527905","title":"Learning to represent programs with heterogeneous graphs","display_name":"Learning to represent programs with heterogeneous graphs","publication_year":2022,"publication_date":"2022-05-16","ids":{"openalex":"https://openalex.org/W4312354494","doi":"https://doi.org/10.1145/3524610.3527905"},"language":"en","primary_location":{"id":"doi:10.1145/3524610.3527905","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524610.3527905","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension","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/A5069561378","display_name":"Kechi Zhang","orcid":"https://orcid.org/0000-0002-3290-0244"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kechi Zhang","raw_affiliation_strings":["Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026622910","display_name":"Wenhan Wang","orcid":"https://orcid.org/0000-0001-7178-8286"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wenhan Wang","raw_affiliation_strings":["Nanyang Technological University, Singapore"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008116021","display_name":"Huangzhao Zhang","orcid":"https://orcid.org/0000-0002-0324-4591"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huangzhao Zhang","raw_affiliation_strings":["Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100447682","display_name":"Ge Li","orcid":"https://orcid.org/0000-0002-5828-0186"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ge Li","raw_affiliation_strings":["Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049100391","display_name":"Zhi Jin","orcid":"https://orcid.org/0000-0003-1087-226X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhi Jin","raw_affiliation_strings":["Peking University, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Peking University, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":16.8892,"has_fulltext":false,"cited_by_count":56,"citation_normalized_percentile":{"value":0.99189281,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"378","last_page":"389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10260","display_name":"Software Engineering Research","score":0.9998999834060669,"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":0.9998999834060669,"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/T10743","display_name":"Software Testing and Debugging Techniques","score":0.9943000078201294,"subfield":{"id":"https://openalex.org/subfields/1712","display_name":"Software"},"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.8030006289482117},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.597550094127655},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.563125491142273},{"id":"https://openalex.org/keywords/source-code","display_name":"Source code","score":0.4773254990577698},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.4710775911808014},{"id":"https://openalex.org/keywords/code-generation","display_name":"Code generation","score":0.43545860052108765},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3642445206642151},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.26203736662864685}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8030006289482117},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.597550094127655},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.563125491142273},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.4773254990577698},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.4710775911808014},{"id":"https://openalex.org/C133162039","wikidata":"https://www.wikidata.org/wiki/Q1061077","display_name":"Code generation","level":3,"score":0.43545860052108765},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3642445206642151},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.26203736662864685},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3524610.3527905","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3524610.3527905","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th IEEE/ACM International Conference on Program Comprehension","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G351474746","display_name":null,"funder_award_id":"62072007, 62192733, 61832009,62192730","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W1501856433","https://openalex.org/W1975563293","https://openalex.org/W2010608861","https://openalex.org/W2064675550","https://openalex.org/W2065053490","https://openalex.org/W2154851992","https://openalex.org/W2157331557","https://openalex.org/W2516621648","https://openalex.org/W2747329762","https://openalex.org/W2809583854","https://openalex.org/W2884276923","https://openalex.org/W2887364112","https://openalex.org/W2890867094","https://openalex.org/W2907492528","https://openalex.org/W2911286998","https://openalex.org/W2943748428","https://openalex.org/W2955426500","https://openalex.org/W2962728167","https://openalex.org/W2963925437","https://openalex.org/W2964150020","https://openalex.org/W2965857891","https://openalex.org/W2999760805","https://openalex.org/W3012871709","https://openalex.org/W3018033251","https://openalex.org/W3034689979","https://openalex.org/W3034716028","https://openalex.org/W3090668753","https://openalex.org/W3104097132","https://openalex.org/W3105735055","https://openalex.org/W3107418514","https://openalex.org/W3161517159","https://openalex.org/W3177441850","https://openalex.org/W3193282971","https://openalex.org/W4246649926"],"related_works":["https://openalex.org/W2787993192","https://openalex.org/W2158269427","https://openalex.org/W4381280689","https://openalex.org/W2847365777","https://openalex.org/W3128025644","https://openalex.org/W2355048207","https://openalex.org/W2750422482","https://openalex.org/W3122369893","https://openalex.org/W2407476586","https://openalex.org/W2750654225"],"abstract_inverted_index":{"Code":[0],"representation,":[1],"which":[2,118],"transforms":[3],"programs":[4],"into":[5,26],"vectors":[6],"with":[7],"semantics,":[8],"is":[9,66],"essential":[10],"for":[11,57,105,183],"source":[12],"code":[13,27,58,106,192],"processing.":[14,150],"We":[15],"have":[16],"witnessed":[17],"the":[18,33,39,43,71,75,78,89,99,103,113,120,123,126,132,145,152,196,202,210,214],"effectiveness":[19],"of":[20,42,74,122,147],"incorporating":[21],"structural":[22,47,162],"information":[23,73,101,148],"(i.e.,":[24,187],"graph)":[25],"representations":[28,140],"in":[29,102,155,199],"recent":[30],"years.":[31],"Specifically,":[32],"abstract":[34],"syntax":[35],"tree":[36],"(AST)":[37],"and":[38,48,51,77,125,166,169,191,217],"AST-augmented":[40],"graph":[41,61,104,116,134],"program":[44,115],"contain":[45],"much":[46],"semantic":[49],"information,":[50,163],"most":[52],"existing":[53,64],"studies":[54],"apply":[55],"them":[56],"representation.":[59,107],"The":[60],"adopted":[62],"by":[63],"approaches":[65],"homogeneous,":[67],"i.e.,":[68],"it":[69],"discards":[70],"type":[72,100,146],"edges":[76,127],"nodes":[79,124],"lying":[80],"within":[81],"AST.":[82],"That":[83],"may":[84],"cause":[85],"plausible":[86],"obstruction":[87],"to":[88,97,138],"representation":[90,203],"model.":[91],"In":[92],"this":[93],"paper,":[94],"we":[95,111,130],"propose":[96,112],"leverage":[98],"To":[108],"be":[109],"specific,":[110],"heterogeneous":[114,133,197],"(HPG),":[117],"provides":[119],"types":[121,154,198],"explicitly.":[128],"Furthermore,":[129],"employ":[131],"transformer":[135],"(HGT)":[136],"architecture":[137],"generate":[139],"based":[141],"on":[142,173,213],"HPG,":[143,156],"considering":[144],"during":[149],"With":[151],"additional":[153],"our":[157],"approach":[158],"can":[159],"capture":[160],"complex":[161],"produce":[164],"accurate":[165],"delicate":[167],"representations,":[168],"finally":[170],"perform":[171],"well":[172],"certain":[174],"tasks.":[175],"Our":[176,205],"in-depth":[177],"evaluations":[178],"upon":[179],"four":[180],"classic":[181],"datasets":[182],"two":[184],"typical":[185],"tasks":[186,216],"method":[188],"name":[189],"prediction":[190],"classification)":[193],"demonstrate":[194],"that":[195],"HPG":[200],"benefit":[201],"models.":[204],"proposed":[206],"HPG+HGT":[207],"also":[208],"outperforms":[209],"SOTA":[211],"baselines":[212],"subject":[215],"datasets.":[218]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":13},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":15},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}