{"id":"W2163293317","doi":"10.1109/hase.2008.14","title":"At What Level of Granularity Should We be Componentizing for Software Reliability?","year":2008,"lang":"en","type":"article","venue":"","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Granularity; Decomposition; Component (thermodynamics); Computer science; Reliability engineering; Reliability (semiconductor); Software system; Software; Component-based software engineering; Architectural pattern; Software construction; Programming language; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001057434,0.0001840837,0.000441299,0.00016698,0.0004230001,0.0001065256,0.001138684,0.0001390165,0.00006750031],"category_scores_gemma":[0.0007802664,0.0001559215,0.000422381,0.0006152533,0.0002908244,0.001143006,0.0007050671,0.0001871368,0.00001792959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001184236,"about_ca_system_score_gemma":0.0001219174,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002011722,"about_ca_topic_score_gemma":0.00007422438,"domain_scores_codex":[0.9974346,0.0001355294,0.0005005918,0.0006752287,0.0007988438,0.0004551803],"domain_scores_gemma":[0.996622,0.00144828,0.0001016176,0.001160752,0.0004977008,0.0001696027],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007724715,0.007179023,0.4225467,0.004989772,0.001003026,0.000169758,0.01827016,0.005719437,0.02449148,0.06209559,0.06394859,0.388814],"study_design_scores_gemma":[0.008055106,0.001572874,0.06787598,0.0007577707,0.0002060231,0.0003066878,0.0011655,0.4061848,0.2665944,0.1179602,0.125673,0.00364771],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1175224,0.0005084889,0.8762262,0.004932364,0.000154985,0.0003802115,0.00002139728,0.0001974415,0.00005650655],"genre_scores_gemma":[0.6816626,0.0009885015,0.3147139,0.0004441383,0.00004470313,0.00005701184,0.00002568227,0.00001844549,0.002045092],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5641401,"threshold_uncertainty_score":0.6358293,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2939605906415504,"score_gpt":0.3513395991599596,"score_spread":0.05737900851840916,"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."}}