{"id":"W2006575153","doi":"10.1109/icst.2013.23","title":"Efficient JavaScript Mutation Testing","year":2013,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Mutation testing; JavaScript; Test suite; Mutation; Programming language; Web application; Process (computing); Set (abstract data type); Focus (optics); Test case; Software engineering; Data mining; Machine learning; Operating system","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0001588344,0.00006749804,0.0000566961,0.00006504665,0.00008198915,0.0001736697,0.0003295894,0.00002369588,0.00001921919],"category_scores_gemma":[0.0005483338,0.000055271,0.0000183054,0.0003192186,0.00001478805,0.0001081462,0.0001105839,0.00005121615,0.000318668],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001853202,"about_ca_system_score_gemma":0.00002029561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004247464,"about_ca_topic_score_gemma":4.108723e-7,"domain_scores_codex":[0.9993576,0.00001953938,0.0001167514,0.0001970635,0.0001440349,0.0001649762],"domain_scores_gemma":[0.9992114,0.0002517515,0.0000368555,0.0003083695,0.0001411959,0.00005040129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[3.577112e-7,0.0001147626,0.008822633,0.00001778923,0.00000737324,0.00001968889,0.0006761164,0.001926059,0.0018119,0.02025944,0.1150304,0.8513135],"study_design_scores_gemma":[0.0000506017,0.00004092584,0.008788317,0.00001605451,8.855146e-7,0.00003690012,0.00000299077,0.9511132,0.001015264,0.03875106,0.00007561588,0.0001081685],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03740062,0.00001722789,0.9325864,0.0003527787,0.0001195555,0.0001180846,4.947403e-8,0.01743875,0.01196657],"genre_scores_gemma":[0.5175262,3.417364e-8,0.4820409,0.0002718236,0.00001279585,0.00001713635,1.547457e-7,0.000002757855,0.0001282379],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9491872,"threshold_uncertainty_score":0.4095938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0277027010756055,"score_gpt":0.2397273919439233,"score_spread":0.2120246908683178,"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."}}