{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004881647,0.00006960388,0.0001322027,0.0001179981,0.0001599474,0.00007620046,0.000260961,0.00004247352,0.000004693198],"category_scores_gemma":[0.004620547,0.00007006331,0.00003532207,0.001361793,0.00004113472,0.0007759331,0.00009327287,0.0000664884,0.000003993301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002058806,"about_ca_system_score_gemma":0.0001086181,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007667886,"about_ca_topic_score_gemma":0.000006193757,"domain_scores_codex":[0.9992012,0.00005512047,0.0002042743,0.0002504371,0.0001602558,0.0001287059],"domain_scores_gemma":[0.9977893,0.0009929269,0.0001914156,0.0003150505,0.0006319993,0.00007926498],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009606277,0.000801758,0.07235657,0.0001992276,0.00154576,0.00001901269,0.3964018,0.01286849,0.004088079,0.180552,0.001933,0.3282737],"study_design_scores_gemma":[0.001383089,0.001178843,0.009324323,0.00008941935,0.0009662339,0.00007311393,0.0303906,0.780576,0.01006364,0.005562779,0.1592436,0.001148351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07719953,0.0004194285,0.9212834,0.0003442493,0.000367863,0.00009934978,0.000001885027,0.00008872466,0.0001955552],"genre_scores_gemma":[0.7863934,0.00002042295,0.2132854,0.0002401105,0.00002788855,0.000007953855,0.000003437561,0.000003299332,0.00001803996],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7677075,"threshold_uncertainty_score":0.553156,"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."}}