{"id":"W6891916858","doi":"10.48550/arxiv.2308.13129","title":"Accelerating Continuous Integration with Parallel Batch Testing","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Reduction (mathematics); Variable (mathematics); Regression testing; Test case; Test (biology); Batch processing; Execution time; Constant (computer programming); System under test","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004022537,0.0003578164,0.0003538174,0.000271401,0.0002627574,0.0003797812,0.001554969,0.0002387654,0.000002685411],"category_scores_gemma":[0.0005138756,0.0003556349,0.00009094298,0.0009760072,0.00007896484,0.0003617998,0.001496295,0.0007354713,0.0000445156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000150332,"about_ca_system_score_gemma":0.0002257548,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007957013,"about_ca_topic_score_gemma":0.00007261044,"domain_scores_codex":[0.9979687,0.0001167922,0.0002317796,0.001163252,0.000127608,0.0003918882],"domain_scores_gemma":[0.9973586,0.000669919,0.000356089,0.001133964,0.0003650565,0.0001163979],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00008651656,0.0003524724,0.2598923,0.0004467333,0.0003610841,0.004946723,0.003158899,0.5303923,0.0001565283,0.1436267,0.01633295,0.04024686],"study_design_scores_gemma":[0.0002264705,0.0001151749,0.003817038,0.0005048826,0.00003489913,0.00002066244,0.00003323271,0.8552912,0.00007235539,0.1393296,0.00002020002,0.0005343633],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08262781,0.00001050564,0.8983606,0.0001023193,0.0002492676,0.0002885649,0.000003627386,0.01706004,0.001297284],"genre_scores_gemma":[0.7683203,0.000008131071,0.2308045,0.00006237796,0.00006618722,0.000004078716,0.00001297873,0.00003048254,0.0006909833],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6856924,"threshold_uncertainty_score":0.9998896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1923784708883698,"score_gpt":0.2156109571248118,"score_spread":0.02323248623644206,"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."}}