{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006160426,0.0005753948,0.0002818172,0.001646141,0.000508307,0.0009195173,0.0009735429,0.000587978,0.001415548],"category_scores_gemma":[0.004450099,0.0005208657,0.000415389,0.0009373641,0.0006921745,0.0009998374,0.00084949,0.0005684337,0.0003499467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001008371,"about_ca_system_score_gemma":0.001041321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00517817,"about_ca_topic_score_gemma":0.004247309,"domain_scores_codex":[0.9993604,0.0001363493,0.00003948573,0.0001465971,0.000248449,0.00006889489],"domain_scores_gemma":[0.9969408,0.001309593,0.0005192339,0.0005923081,0.0005643466,0.00007364767],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0008758421,0.0005664701,0.06058516,0.0005033691,0.0001404715,0.002843577,0.002810444,0.2797712,0.1942524,0.01402602,0.003068228,0.4405568],"study_design_scores_gemma":[0.00004029599,0.0002518987,0.01302994,0.00005664282,0.00006218387,0.0004690582,0.0002320582,0.841701,0.1336173,0.007559297,0.002931287,0.00004914469],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.6424929,0.0001872894,0.3397285,0.00009872628,0.00002562425,0.0001007709,0.000220914,0.01506505,0.002080303],"genre_scores_gemma":[0.8980718,0.00005822035,0.09997782,0.00002209549,0.000004560405,0.00005347457,0.0003250217,0.0005856444,0.000901375],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.00517817,"threshold_uncertainty_score":0.01029611,"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."}}