{"id":"W3092300773","doi":"10.1002/spe.2907","title":"Practical dynamic reconstruction of control flow graphs","year":2020,"lang":"en","type":"article","venue":"Software Practice and Experience","topic":"Parallel Computing and Optimization Techniques","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico","keywords":"Executable; Computer science; Debugging; Spec#; Programming language; Control flow graph; Dataflow; Control flow; Symbolic execution; Static analysis; Machine code; Scripting language; Binary number; Data-flow analysis; Control flow analysis; Code (set theory); Theoretical computer science; Compiler; Data flow diagram; Software; Arithmetic; Programming paradigm; Declarative programming","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":[0.0001871524,0.0001008711,0.0001546622,0.00004257677,0.0001105129,0.00008690783,0.000235459,0.0000579102,0.000007480581],"category_scores_gemma":[0.002094558,0.00009697256,0.00003436543,0.0003114439,0.0001106726,0.001493666,0.0001017181,0.0001520879,0.000005067795],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009145886,"about_ca_system_score_gemma":0.000063739,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001070585,"about_ca_topic_score_gemma":3.214763e-7,"domain_scores_codex":[0.9989905,0.0001165407,0.0002312287,0.0003271346,0.0001877388,0.0001469077],"domain_scores_gemma":[0.9988298,0.0004591195,0.0002096181,0.0002153165,0.0001721,0.0001140832],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006542108,0.000502868,0.007968256,0.000221602,0.0001783874,0.0001665819,0.05927597,0.004458285,0.003210668,0.05412954,0.00398919,0.8652444],"study_design_scores_gemma":[0.0009101283,0.0006038641,0.0004507338,0.00006086729,0.00003496911,0.0006489,0.001769078,0.9833658,0.002538216,0.003072428,0.006069466,0.0004755562],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003496956,0.0001827409,0.9901022,0.00546424,0.0001091194,0.0001066155,0.000001410102,0.0003377437,0.0001990043],"genre_scores_gemma":[0.448402,0.000138585,0.5503592,0.001075874,0.000009199887,0.000008195095,4.739911e-7,0.000003352136,0.000003124676],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.9789075,"threshold_uncertainty_score":0.3954426,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01764990418475308,"score_gpt":0.2980036989792894,"score_spread":0.2803537947945363,"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."}}