{"id":"W3102206389","doi":"10.1145/3419604.3419628","title":"Test Generation Tool for Modified Condition/Decision Coverage","year":2020,"lang":"en","type":"article","venue":"","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Traceability; Model-based testing; Integration testing; Code coverage; Test strategy; White-box testing; Dataflow; Extended finite-state machine; Non-regression testing; Keyword-driven testing; Manual testing; Reliability engineering; Software performance testing; Test case; Software; Finite-state machine; Software system; Algorithm; Software engineering; Programming language; Engineering; Software construction; Machine learning","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":[0.001199019,0.001272555,0.0005691496,0.002321669,0.0003440349,0.001040562,0.001529603,0.001288027,0.01908406],"category_scores_gemma":[0.006289598,0.0005132236,0.00123382,0.001042455,0.0005914549,0.001174638,0.001003888,0.001085345,0.003151681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005921592,"about_ca_system_score_gemma":0.0008634354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001592934,"about_ca_topic_score_gemma":0.001039912,"domain_scores_codex":[0.9985771,0.0003582554,0.0001456614,0.0002472223,0.0005491393,0.0001225663],"domain_scores_gemma":[0.99729,0.001789195,0.0001465162,0.000343751,0.0003895884,0.00004094876],"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":[0.0009210097,0.0005715498,0.004904726,0.001116975,0.0001445862,0.002338081,0.0005154405,0.1272091,0.07497027,0.09028579,0.04888025,0.6481424],"study_design_scores_gemma":[0.0003181431,0.0002637374,0.0008991444,0.0001294982,0.00007324175,0.001213868,0.00004616089,0.8359752,0.081894,0.03154741,0.04757065,0.00006905419],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007928079,0.00006127276,0.9387729,0.000103042,0.00004389386,0.0002144778,0.001023602,0.04693285,0.004919906],"genre_scores_gemma":[0.2024841,0.0001319984,0.7776916,0.0002354639,0.00004678435,0.0009304965,0.006605626,0.006037968,0.00583593],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01908406,"threshold_uncertainty_score":0.06384254,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05601324452544399,"score_gpt":0.2919229312983528,"score_spread":0.2359096867729089,"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."}}