{"id":"W4392942125","doi":"10.1109/bcd57833.2023.10466329","title":"PyTPU: Migration of Python Code for Heterogenous Acceleration with Automated Test Generation","year":2023,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"","keywords":"Python (programming language); Computer science; Programming language; Unit testing; Software","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005196527,0.002149143,0.0007774734,0.002091645,0.0008210388,0.001856973,0.004293623,0.00141307,0.008005891],"category_scores_gemma":[0.02211582,0.001680854,0.002137136,0.000864766,0.002656329,0.003652183,0.004211045,0.002785825,0.004160327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001256693,"about_ca_system_score_gemma":0.004020307,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003914332,"about_ca_topic_score_gemma":0.003034176,"domain_scores_codex":[0.9948474,0.001332136,0.0005739508,0.0009832612,0.001668231,0.0005949533],"domain_scores_gemma":[0.9888313,0.003732541,0.001178179,0.004307246,0.001539936,0.0004107657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002717599,0.001215156,0.04857095,0.002156348,0.0006023823,0.003802888,0.003680351,0.07233202,0.08021352,0.02905964,0.1262163,0.6294329],"study_design_scores_gemma":[0.0005486791,0.0009378042,0.01372066,0.0005681876,0.0002001351,0.001985944,0.0005041358,0.6485835,0.1977779,0.03148882,0.1032378,0.0004463334],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.04042208,0.0002097659,0.4753833,0.0003791258,0.00016834,0.0006286118,0.001592814,0.4773377,0.003878276],"genre_scores_gemma":[0.3892753,0.0002812478,0.5178363,0.0009085653,0.00009288849,0.00143141,0.008796443,0.07553583,0.005842026],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008005891,"threshold_uncertainty_score":0.02748221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06133012185637991,"score_gpt":0.3012295787611269,"score_spread":0.239899456904747,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}