{"id":"W2144847134","doi":"10.1145/1370042.1370056","title":"Automated instrumentation of contracts and scenarios for requirements validation in .net","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced Software Engineering Methodologies","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Non-functional requirement; Unified Modeling Language; Software requirements specification; Functional requirement; Instrumentation (computer programming); Software engineering; Functional specification; System requirements specification; Metric (unit); Formal specification; Reliability engineering; Systems engineering; Non-functional testing; Matching (statistics); Requirements engineering; Requirements management; Programming language; Software; Software system; Software development; Engineering; Software design","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":[0.0002095249,0.00004660903,0.0000869021,0.00007477732,0.0000199048,0.000007005337,0.0001161948,0.00002492356,5.593639e-7],"category_scores_gemma":[0.0004971927,0.00004486155,0.000007988496,0.0001172936,0.0000185017,0.000435611,0.0000468929,0.00002043794,3.059789e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002225246,"about_ca_system_score_gemma":0.00001570023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009929365,"about_ca_topic_score_gemma":0.000001832415,"domain_scores_codex":[0.999545,0.00002731122,0.0001534127,0.0001170246,0.00007129269,0.00008597667],"domain_scores_gemma":[0.9995406,0.0002407495,0.00005440182,0.0001139303,0.00003555122,0.0000147173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001402392,0.0003380285,0.06080463,0.0003344619,0.00007632784,0.00002243635,0.007978939,0.4517345,0.2518855,0.03896469,0.0008854704,0.1868348],"study_design_scores_gemma":[0.002795011,0.0002864475,0.1483267,0.00005921175,0.000004361795,0.00002143395,0.00005842233,0.5801637,0.253706,0.01423081,0.00007473165,0.0002731831],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.338356,0.000009427082,0.6612258,0.00003470517,0.00005755064,0.0001268852,4.773372e-7,0.0001761102,0.00001306035],"genre_scores_gemma":[0.5152169,0.000007193542,0.4847409,0.0000130875,0.00000183291,0.000008104888,0.000001774686,0.000001646772,0.000008471325],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.1865616,"threshold_uncertainty_score":0.1829401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0791072290790121,"score_gpt":0.3358705170490376,"score_spread":0.2567632879700256,"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."}}