{"id":"https://openalex.org/W7171671102","doi":"https://doi.org/10.1145/3794763.3794808","title":"SCOPE:Tree-based Self-Correcting Online Log Parsing via Syntactic-Semantic Collaboration","display_name":"SCOPE:Tree-based Self-Correcting Online Log Parsing via Syntactic-Semantic Collaboration","publication_year":2026,"publication_date":"2026-04-12","ids":{"openalex":"https://openalex.org/W7171671102","doi":"https://doi.org/10.1145/3794763.3794808"},"language":null,"primary_location":{"id":"doi:10.1145/3794763.3794808","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3794763.3794808","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 34th IEEE/ACM International Conference on Program Comprehension","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3794763.3794808","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052273729","display_name":"Dongyi Fan","orcid":"https://orcid.org/0009-0008-1345-6644"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongyi Fan","raw_affiliation_strings":["Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-1345-6644","affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040897754","display_name":"Suqiong Zhang","orcid":"https://orcid.org/0000-0002-6365-0727"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Suqiong Zhang","raw_affiliation_strings":["Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-6365-0727","affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107936194","display_name":"Lili He","orcid":"https://orcid.org/0009-0008-4571-3553"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lili He","raw_affiliation_strings":["Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0008-4571-3553","affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5138629585","display_name":"Ming Liu","orcid":"https://orcid.org/0009-0004-8527-7339"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Liu","raw_affiliation_strings":["Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0004-8527-7339","affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5108968551","display_name":"Yifan Huo","orcid":"https://orcid.org/0009-0006-8438-4700"},"institutions":[{"id":"https://openalex.org/I1328775524","display_name":"Zhejiang Sci-Tech University","ror":"https://ror.org/03893we55","country_code":"CN","type":"education","lineage":["https://openalex.org/I1328775524"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yifan Huo","raw_affiliation_strings":["Zhejiang Sci-Tech University, Hangzhou, China"],"raw_orcid":"https://orcid.org/0009-0006-8438-4700","affiliations":[{"raw_affiliation_string":"Zhejiang Sci-Tech University, Hangzhou, China","institution_ids":["https://openalex.org/I1328775524"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I1328775524"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"171","last_page":"182"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/parsing","display_name":"Parsing","score":0.4009000062942505},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.2973000109195709},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.2759000062942505},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.27469998598098755}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6717000007629395},{"id":"https://openalex.org/C186644900","wikidata":"https://www.wikidata.org/wiki/Q194152","display_name":"Parsing","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39469999074935913},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3244999945163727},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2973000109195709},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.27469998598098755},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2669000029563904},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.2567000091075897},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.25060001015663147}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3794763.3794808","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3794763.3794808","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 34th IEEE/ACM International Conference on Program Comprehension","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3794763.3794808","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3794763.3794808","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2026 34th IEEE/ACM International Conference on Program Comprehension","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2015979301","https://openalex.org/W2039157918","https://openalex.org/W2208211896","https://openalex.org/W2527994611","https://openalex.org/W2754665629","https://openalex.org/W2767094836","https://openalex.org/W2903799441","https://openalex.org/W2946249231","https://openalex.org/W2953332704","https://openalex.org/W2963999143","https://openalex.org/W3183619936","https://openalex.org/W3207794047","https://openalex.org/W4205965165","https://openalex.org/W4226483168","https://openalex.org/W4284688717","https://openalex.org/W4284692184","https://openalex.org/W4367146761","https://openalex.org/W4384345672","https://openalex.org/W4384345673","https://openalex.org/W4386065596","https://openalex.org/W4386076140","https://openalex.org/W4388212317","https://openalex.org/W4394769544","https://openalex.org/W4400583111","https://openalex.org/W4401567249","https://openalex.org/W4401863940","https://openalex.org/W4402208708","https://openalex.org/W4402270600","https://openalex.org/W4402443006","https://openalex.org/W4411450161","https://openalex.org/W4411522841","https://openalex.org/W7133224126"],"related_works":[],"abstract_inverted_index":{"Log":[0],"parsing":[1,58],"is":[2,118],"a":[3,72,90,98,103,122,144],"critical":[4],"step":[5],"for":[6,112],"automated":[7],"log":[8,57],"analysis":[9],"in":[10,22,89,162],"complex":[11,127],"systems.":[12],"Traditional":[13],"heuristic-based":[14],"methods":[15,161],"offer":[16],"high":[17,41,141],"efficiency":[18,147],"but":[19,39],"are":[20,171],"limited":[21],"accuracy":[23,35,164],"due":[24],"to":[25,124,174],"overlooking":[26],"semantic":[27,37],"context.":[28],"In":[29],"contrast,":[30],"recent":[31],"LLM-based":[32,68],"parsers":[33],"improve":[34],"via":[36],"understanding":[38],"incur":[40],"latency":[42],"from":[43,82],"frequent":[44],"model":[45,106],"calls.":[46],"To":[47],"address":[48],"this,":[49],"we":[50],"propose":[51],"SCOPE,":[52],"the":[53,62,116],"first":[54,107],"self-correcting":[55],"online":[56],"method":[59],"that":[60,77,157],"integrates":[61],"strengths":[63],"of":[64],"both":[65,83,163],"heuristic":[66],"and":[67,85,148,165,169],"paradigms.":[69],"SCOPE":[70,158],"introduces":[71],"novel":[73],"bi-directional":[74],"tree":[75],"structure":[76],"enables":[78],"efficient":[79],"template":[80],"matching":[81,93],"forward":[84],"reverse":[86],"directions,":[87],"resulting":[88],"higher":[91],"overall":[92],"rate.":[94],"Additionally,":[95],"it":[96],"adopts":[97],"two-stage":[99],"syntactic-semantic":[100],"collaboration":[101],"framework:":[102],"lightweight":[104],"NLP":[105],"utilizes":[108],"part-of-speech":[109],"(POS)":[110],"information":[111],"syntax-based":[113],"matching,":[114],"while":[115,139],"LLM":[117,136],"selectively":[119],"invoked":[120],"as":[121],"fallback":[123],"handle":[125],"semantically":[126],"cases":[128],"when":[129],"uncertainty":[130],"remains.":[131],"This":[132],"design":[133],"significantly":[134],"reduces":[135],"API":[137],"usage":[138],"maintaining":[140],"accuracy,":[142],"achieving":[143],"balance":[145],"between":[146],"effectiveness.":[149],"Extensive":[150],"evaluations":[151],"on":[152],"diverse":[153],"benchmark":[154],"datasets":[155,170],"show":[156],"outperforms":[159],"state-of-the-art":[160],"efficiency.":[166],"The":[167],"implementation":[168],"publicly":[172],"released":[173],"facilitate":[175],"further":[176],"research.":[177]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2026-07-30T00:00:00"}
