{"id":"W2111584600","doi":"10.1002/stvr.452","title":"On reducing test length for FSMs with extra states","year":2011,"lang":"en","type":"article","venue":"Software Testing Verification and Reliability","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Computer Research Institute of Montréal","funders":"","keywords":"Tree traversal; Test suite; Computer science; Reduction (mathematics); Set (abstract data type); Algorithm; Finite-state machine; Test set; Implementation; Test case; Theoretical computer science; Mathematics; Programming language; Artificial intelligence","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":[0.002114302,0.0007993649,0.001017807,0.001086105,0.0006148038,0.0006593789,0.001660067,0.0006184493,0.002591542],"category_scores_gemma":[0.01988158,0.0005111171,0.00106263,0.0008725713,0.0009857932,0.002536883,0.001695412,0.001922815,0.0003787552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127882,"about_ca_system_score_gemma":0.001517172,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001404347,"about_ca_topic_score_gemma":0.002185384,"domain_scores_codex":[0.9966927,0.001372622,0.0002003307,0.0003477031,0.001066304,0.0003204269],"domain_scores_gemma":[0.9642112,0.02630382,0.002576049,0.004277951,0.001989783,0.000641047],"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":[0.002294017,0.0005101995,0.005706168,0.0004254445,0.0001380664,0.0004867791,0.0003812585,0.3548139,0.0684255,0.01976239,0.003020393,0.5440359],"study_design_scores_gemma":[0.0001836928,0.001092607,0.001727542,0.00004948177,0.00007101305,0.0002876182,0.00008066095,0.9344681,0.03316031,0.02622076,0.00263116,0.00002703425],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2668244,0.0004150608,0.7259353,0.00067202,0.00006286509,0.0002182945,0.0001364565,0.003219974,0.002515689],"genre_scores_gemma":[0.6431977,0.0002001668,0.3531735,0.0002421823,0.00009196489,0.0003153245,0.0005145087,0.000516007,0.001748637],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002591542,"threshold_uncertainty_score":0.01118159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04516024558319632,"score_gpt":0.2535739498862984,"score_spread":0.2084137043031021,"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."}}