{"id":"W3149550336","doi":"10.1109/raise.2012.6227969","title":"Predicting mutation score using source code and test suite metrics","year":2012,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Test suite; Computer science; Mutation; Mutation testing; Source code; Suite; Code coverage; Test case; Process (computing); Code (set theory); Reliability engineering; Programming language; Machine learning; Software; Set (abstract data type); Engineering; Biology; Genetics","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":[0.002015788,0.001349461,0.0008296457,0.007791116,0.000224411,0.0009221868,0.0006934564,0.001309912,0.0005168403],"category_scores_gemma":[0.02048316,0.0002745758,0.0006572696,0.00273405,0.0002890911,0.00132764,0.0004546664,0.0006501203,0.0004637334],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006228624,"about_ca_system_score_gemma":0.0005854091,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003510112,"about_ca_topic_score_gemma":0.00399522,"domain_scores_codex":[0.9981492,0.000438039,0.0001771019,0.0003106959,0.0008036841,0.0001213717],"domain_scores_gemma":[0.9821034,0.009723647,0.002839687,0.0008206629,0.003917618,0.0005949507],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002814907,0.0006826024,0.4073517,0.0001477536,0.0002733858,0.0004049413,0.000069298,0.2968413,0.01802536,0.0009083126,0.002524319,0.2724896],"study_design_scores_gemma":[0.00001143406,0.0001267096,0.02972731,0.000009666934,0.00003108952,0.0001304059,0.00001452926,0.9632118,0.005472694,0.001013593,0.0002304443,0.00002023211],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8203655,0.0004456964,0.1724551,0.0002777807,0.00003287587,0.0001167113,0.001476844,0.00362202,0.001207495],"genre_scores_gemma":[0.9305713,0.0001401049,0.06611601,0.00003381013,0.0000257016,0.00006714181,0.002588878,0.00009913799,0.0003578967],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007791116,"threshold_uncertainty_score":0.01066059,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05832407227421543,"score_gpt":0.2908110474789894,"score_spread":0.232486975204774,"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."}}