{"id":"W3211076835","doi":"10.1109/rew53955.2021.00012","title":"Generating Sequence Diagram from Natural Language Requirements","year":2021,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Alberta Innovates","keywords":"Sequence diagram; Computer science; Unified Modeling Language; Communication diagram; Correctness; Completeness (order theory); Class diagram; Programming language; Applications of UML; Use Case Diagram; UML tool; Natural language; Sequence (biology); Natural language processing; Software engineering; Software","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":[0.0001166528,0.00007695299,0.00007541929,0.00003084204,0.00005423176,0.0002239981,0.0005133279,0.00002702339,0.00009134719],"category_scores_gemma":[0.0006409083,0.00007070601,0.00002990092,0.0003099164,0.00001146473,0.0003109876,0.0003818064,0.000143896,0.00009855291],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000542499,"about_ca_system_score_gemma":0.00007291666,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001733495,"about_ca_topic_score_gemma":0.0000286436,"domain_scores_codex":[0.9989608,0.00003742486,0.0001044718,0.0003171246,0.0003341788,0.0002459915],"domain_scores_gemma":[0.9990695,0.0002642058,0.00001402689,0.0005116913,0.00007169115,0.00006892581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001157189,0.00005584953,0.01882477,0.00001786135,0.00005704906,0.001351657,0.001946949,0.0009418307,0.687194,0.003684329,0.00264608,0.2832784],"study_design_scores_gemma":[0.0003513319,0.00002154466,0.01664461,0.0000393797,0.000002774051,0.00002941008,0.00008331826,0.7083098,0.2732458,0.0002511036,0.0006453324,0.0003755913],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5835611,0.000913794,0.4139189,0.000290986,0.0005517884,0.00004516997,0.000002195167,0.0004343305,0.0002816753],"genre_scores_gemma":[0.7898637,0.000004287257,0.2087088,0.0002622253,0.00009249199,0.000005983586,0.00001061809,0.000005807275,0.001046087],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.707368,"threshold_uncertainty_score":0.2883308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03411350203033933,"score_gpt":0.3147973851656794,"score_spread":0.2806838831353401,"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."}}