{"id":"W2788598677","doi":"","title":"Mapping features to source code in dynamically configured avionics software","year":2012,"lang":"en","type":"article","venue":"PolyPublie (École Polytechnique de Montréal)","topic":"Software Reliability and Analysis Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Consortium de Recherche et d’innovation en Aérospatiale au Québec","keywords":"Computer science; Program comprehension; Static program analysis; Avionics; Software; Feature (linguistics); Source code; Software system; Software engineering; Avionics software; Code (set theory); Reverse engineering; Feature model; Software construction; Software development; Programming language; Engineering; Set (abstract data type)","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001848396,0.0003470019,0.0004775962,0.0009531382,0.0002513093,0.0003959213,0.001841815,0.0003451212,0.00002468864],"category_scores_gemma":[0.001361368,0.0003457567,0.0002250023,0.002210348,0.00008016353,0.0006987998,0.0008321119,0.0007960607,0.00007552662],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008159903,"about_ca_system_score_gemma":0.000289102,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004119301,"about_ca_topic_score_gemma":0.00278502,"domain_scores_codex":[0.9962211,0.0003213906,0.000565479,0.0006704075,0.0007624226,0.001459195],"domain_scores_gemma":[0.9970411,0.0004546047,0.0001270285,0.001441165,0.0001834501,0.0007526536],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001037473,0.00137302,0.5906146,0.0001471286,0.0001315644,0.0001006154,0.005669243,0.02064877,0.009496938,0.05165038,0.004616623,0.3154473],"study_design_scores_gemma":[0.0009049293,0.0001880102,0.6254076,0.0002375547,0.00001987751,0.0001806651,0.0003565729,0.3417896,0.005327445,0.004343461,0.0198344,0.001409878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09871822,0.0009324938,0.8929473,0.005717675,0.00009562865,0.0005703476,0.00001382234,0.0008828326,0.0001216669],"genre_scores_gemma":[0.7205695,0.00006192101,0.2757601,0.002455047,0.00008536332,0.0002938459,0.00001385532,0.0000374184,0.000722935],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6218513,"threshold_uncertainty_score":0.9998994,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0122718085584116,"score_gpt":0.2555039640419555,"score_spread":0.2432321554835439,"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."}}