{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002535974,0.00008976866,0.0001038608,0.0001362613,0.0001084472,0.0001198719,0.0002008181,0.00004839588,0.0000010309],"category_scores_gemma":[0.0001683976,0.00007226367,0.00002620636,0.0004920534,0.00001582404,0.0002694974,0.00003423918,0.00002739058,0.000006064267],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002186449,"about_ca_system_score_gemma":0.00004824301,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007154071,"about_ca_topic_score_gemma":0.0001562048,"domain_scores_codex":[0.9992566,0.00002019902,0.0001910703,0.0002305557,0.0001593102,0.0001422887],"domain_scores_gemma":[0.9991435,0.0002290191,0.00009879658,0.000290437,0.000210778,0.00002741504],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006205004,0.0005549951,0.03642923,0.0002539708,0.00007548885,0.00001644759,0.003729043,0.01190084,0.4331935,0.01188116,0.4056382,0.09626504],"study_design_scores_gemma":[0.0001483805,0.0004998241,0.001819165,0.00001651787,0.000004187156,0.000007788276,0.000002034145,0.9046909,0.09148144,0.00101701,0.0002171202,0.00009563425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1575374,0.000006058376,0.8165063,0.0004087572,0.00005916459,0.0002984059,0.000007416628,0.02512579,0.0000507056],"genre_scores_gemma":[0.6991139,0.000002456725,0.300547,0.00009195001,0.00003478144,0.00007501026,0.00005724522,0.0000101225,0.00006750938],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8927901,"threshold_uncertainty_score":0.2946827,"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."}}