{"id":"W4248647026","doi":"10.1002/stvr.410","title":"Improving the coverage criteria of UML state machines using data flow analysis","year":2009,"lang":"en","type":"article","venue":"Software Testing Verification and Reliability","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":16,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Unified Modeling Language; Guard (computer science); Finite-state machine; Data mining; Data flow diagram; Test suite; Context (archaeology); State (computer science); Control flow; Data-flow analysis; Tree (set theory); Test case; Algorithm; Machine learning; Database; Programming language; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006722432,0.001005506,0.0008688701,0.00671875,0.000487898,0.001571719,0.000878434,0.0009058358,0.0009309474],"category_scores_gemma":[0.04123078,0.0004678388,0.001149456,0.001559624,0.001143442,0.002175453,0.001321197,0.0006263652,0.0001311698],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00167502,"about_ca_system_score_gemma":0.001255769,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004276224,"about_ca_topic_score_gemma":0.002727206,"domain_scores_codex":[0.9919177,0.004424823,0.0004673693,0.0004991555,0.002293087,0.0003977865],"domain_scores_gemma":[0.9326225,0.0572468,0.003457719,0.001940481,0.004344654,0.00038783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008056375,0.0004528644,0.04831415,0.0005080661,0.0001897254,0.0006105079,0.001075402,0.5931373,0.03975538,0.03034105,0.001195753,0.2836141],"study_design_scores_gemma":[0.00003130202,0.0001408511,0.002500275,0.00004821575,0.00003564053,0.00007986661,0.00006091521,0.9727895,0.01576553,0.007932138,0.0005965186,0.00001927684],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3459426,0.0002879254,0.6498095,0.0002648288,0.000009750065,0.0002270916,0.0002686659,0.001520867,0.001668791],"genre_scores_gemma":[0.8485721,0.00008268785,0.1504214,0.00003845288,0.00001147468,0.0001969676,0.0003759172,0.00009891789,0.0002019638],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006722432,"threshold_uncertainty_score":0.03555208,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04962212616320409,"score_gpt":0.3113156837427992,"score_spread":0.2616935575795951,"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."}}