{"id":"W2269942371","doi":"10.1002/spe.2388","title":"SafeType: detecting type violations for type‐basedalias analysis of C","year":2015,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; IBM (Canada)","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Alias; Computer science; Compiler; Programming language; Memory safety; Type inference; Static analysis; Benchmark (surveying); Type safety; Spec#; Context (archaeology); Java; Compile time; Database; Inference; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003722863,0.001630164,0.0007226811,0.003015147,0.001427229,0.002333147,0.002444393,0.00139853,0.004583688],"category_scores_gemma":[0.0181192,0.001016859,0.001414675,0.00122791,0.002290777,0.003354435,0.002622376,0.001870687,0.001855876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00152093,"about_ca_system_score_gemma":0.003694613,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006044058,"about_ca_topic_score_gemma":0.004374598,"domain_scores_codex":[0.9938877,0.001318292,0.0004320166,0.0009432333,0.002862838,0.0005559077],"domain_scores_gemma":[0.9850612,0.006398286,0.001977998,0.003676747,0.002660904,0.0002248019],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002429144,0.0003885843,0.04965004,0.001214461,0.0004094256,0.001231958,0.001449843,0.1062915,0.0938781,0.09959884,0.06181351,0.5816447],"study_design_scores_gemma":[0.000123436,0.0003247722,0.005371845,0.0002227175,0.0001149681,0.0006373824,0.0001841174,0.7076536,0.198241,0.05419207,0.03272575,0.0002083462],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07630605,0.0004009872,0.801333,0.0004717292,0.0001380833,0.0002016903,0.0008860431,0.111935,0.008327479],"genre_scores_gemma":[0.58789,0.0002291821,0.3975489,0.0005485517,0.0001013528,0.0001970173,0.001461677,0.007917655,0.004105657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006044058,"threshold_uncertainty_score":0.01968861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1252414425623855,"score_gpt":0.3961707338653774,"score_spread":0.2709292913029919,"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."}}