{"id":"https://openalex.org/W7164044531","doi":"https://doi.org/10.1145/3748522.3779923","title":"Partial Evaluation for Pandas in Python","display_name":"Partial Evaluation for Pandas in Python","publication_year":2026,"publication_date":"2026-03-23","ids":{"openalex":"https://openalex.org/W7164044531","doi":"https://doi.org/10.1145/3748522.3779923"},"language":null,"primary_location":{"id":"doi:10.1145/3748522.3779923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779923","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 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3748522.3779923","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138246506","display_name":"Xavier Sebastian Adettu","orcid":"https://orcid.org/0009-0006-5986-7380"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Xavier Sebastian Adettu","raw_affiliation_strings":["Computer Science, University of Wisconsin -- Milwaukee, Milwaukee, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0009-0006-5986-7380","affiliations":[{"raw_affiliation_string":"Computer Science, University of Wisconsin -- Milwaukee, Milwaukee, Wisconsin, USA","institution_ids":["https://openalex.org/I43579087"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010584684","display_name":"Tian Zhao","orcid":"https://orcid.org/0000-0001-6456-9763"},"institutions":[{"id":"https://openalex.org/I43579087","display_name":"University of Wisconsin\u2013Milwaukee","ror":"https://ror.org/031q21x57","country_code":"US","type":"education","lineage":["https://openalex.org/I43579087"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tian Zhao","raw_affiliation_strings":["Computer Science, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA"],"raw_orcid":"https://orcid.org/0000-0001-6456-9763","affiliations":[{"raw_affiliation_string":"Computer Science, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA","institution_ids":["https://openalex.org/I43579087"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5138246506"],"corresponding_institution_ids":["https://openalex.org/I43579087"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.96727497,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1332","last_page":"1334"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.4571000039577484,"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"}},"topics":[{"id":"https://openalex.org/T13650","display_name":"Computational Physics and Python Applications","score":0.4571000039577484,"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/T10054","display_name":"Parallel Computing and Optimization Techniques","score":0.24779999256134033,"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/T10260","display_name":"Software Engineering Research","score":0.019300000742077827,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.8932999968528748},{"id":"https://openalex.org/keywords/interpreter","display_name":"Interpreter","score":0.5663999915122986},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.46880000829696655},{"id":"https://openalex.org/keywords/partial-evaluation","display_name":"Partial evaluation","score":0.3977000117301941},{"id":"https://openalex.org/keywords/constant","display_name":"Constant (computer programming)","score":0.3472000062465668},{"id":"https://openalex.org/keywords/troubleshooting","display_name":"Troubleshooting","score":0.29429998993873596}],"concepts":[{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.8932999968528748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7439000010490417},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.6693000197410583},{"id":"https://openalex.org/C122783720","wikidata":"https://www.wikidata.org/wiki/Q183065","display_name":"Interpreter","level":2,"score":0.5663999915122986},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.46880000829696655},{"id":"https://openalex.org/C195701839","wikidata":"https://www.wikidata.org/wiki/Q4008398","display_name":"Partial evaluation","level":2,"score":0.3977000117301941},{"id":"https://openalex.org/C2777027219","wikidata":"https://www.wikidata.org/wiki/Q1284190","display_name":"Constant (computer programming)","level":2,"score":0.3472000062465668},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3221000134944916},{"id":"https://openalex.org/C147494362","wikidata":"https://www.wikidata.org/wiki/Q2078905","display_name":"Troubleshooting","level":2,"score":0.29429998993873596},{"id":"https://openalex.org/C92966194","wikidata":"https://www.wikidata.org/wiki/Q651794","display_name":"Compiled language","level":4,"score":0.2904999852180481},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2896000146865845},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.28189998865127563},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.27790001034736633},{"id":"https://openalex.org/C169590947","wikidata":"https://www.wikidata.org/wiki/Q47506","display_name":"Compiler","level":2,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3748522.3779923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779923","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 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3748522.3779923","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3748522.3779923","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 41st ACM/SIGAPP Symposium on Applied Computing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1991079885","https://openalex.org/W2046701033","https://openalex.org/W2058958439","https://openalex.org/W2095594146","https://openalex.org/W2154697693","https://openalex.org/W2342249984","https://openalex.org/W2527672088","https://openalex.org/W3035965352","https://openalex.org/W3082494217","https://openalex.org/W4393183688"],"related_works":[],"abstract_inverted_index":{"Pandas":[0,46,111],"programs":[1,99],"often":[2],"perform":[3],"more":[4],"Python":[5,42],"level":[6],"work":[7,75],"than":[8],"necessary":[9],"due":[10],"to":[11,61,72,102],"row-wise":[12],"apply":[13,92],"calls,":[14],"small":[15],"control":[16],"loops,":[17],"and":[18,26,64,67,77,91],"repeated":[19],"constant":[20,85],"computations.":[21],"These":[22],"patterns":[23],"break":[24],"vectorization":[25],"introduce":[27],"significant":[28],"interpreter":[29],"overhead":[30],"on":[31,105],"large":[32],"datasets.":[33],"We":[34],"present":[35],"a":[36,53,57],"lightweight":[37],"partial":[38],"evaluation":[39],"framework":[40],"for":[41],"that":[43],"automatically":[44],"simplifies":[45],"code":[47],"before":[48],"execution.":[49],"The":[50,82],"system":[51],"uses":[52],"compact":[54],"Pandas-oriented":[55],"DSL,":[56],"two-point":[58],"binding-time":[59],"analysis":[60],"separate":[62],"static":[63,74],"dynamic":[65],"expressions,":[66],"an":[68],"online":[69],"interpreter-based":[70],"specializer":[71],"execute":[73],"early":[76],"emit":[78],"optimized":[79],"residual":[80],"code.":[81],"prototype":[83],"performs":[84],"folding,":[86],"loop":[87],"unrolling,":[88],"UDF":[89],"inlining,":[90],"fusion.":[93],"Across":[94],"synthetic":[95],"workloads,":[96],"the":[97],"specialized":[98],"achieve":[100],"up":[101],"112\u00d7":[103],"speedups":[104],"apply-heavy":[106],"pipelines":[107],"while":[108],"preserving":[109],"full":[110],"semantics.":[112]},"counts_by_year":[],"updated_date":"2026-06-10T14:10:52.464848","created_date":"2026-06-10T00:00:00"}