{"id":"W2080534028","doi":"10.1145/1181775.1181779","title":"Questions programmers ask during software evolution tasks","year":2006,"lang":"en","type":"article","venue":"","topic":"Software Engineering Research","field":"Computer Science","cited_by":259,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Programmer; Categorization; Task (project management); Context (archaeology); Ask price; Program comprehension; Human–computer interaction; Focus (optics); Code (set theory); Software; Data science; Software engineering; Programming language; Software system; 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":[0.01274581,0.0008824803,0.0006978482,0.001520331,0.002706377,0.002766954,0.001273,0.004913435,0.003143801],"category_scores_gemma":[0.1013633,0.0008862882,0.0006221481,0.0009693312,0.00226836,0.005535451,0.00324924,0.002461069,0.0008459605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001068569,"about_ca_system_score_gemma":0.001213086,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001967105,"about_ca_topic_score_gemma":0.001636679,"domain_scores_codex":[0.9838662,0.01153577,0.0008348891,0.001092963,0.001342307,0.001327972],"domain_scores_gemma":[0.8516256,0.1297255,0.008048789,0.002536544,0.00506192,0.003001624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0004828842,0.0002605054,0.07568966,0.0006923306,0.00004273702,0.001143356,0.8600051,0.0005940327,0.01240773,0.002395427,0.004159131,0.04212712],"study_design_scores_gemma":[0.0002031724,0.001518497,0.084533,0.0008333686,0.0001138718,0.002732316,0.8105723,0.006269667,0.0087317,0.008353037,0.07585242,0.0002866435],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9672258,0.0005795506,0.02176919,0.003011659,0.00005315793,0.0002218954,0.0001705212,0.0004126622,0.00655567],"genre_scores_gemma":[0.9831199,0.0005236901,0.01226419,0.001268241,0.0000511561,0.0002744585,0.000210238,0.0001239655,0.002164201],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01274581,"threshold_uncertainty_score":0.06740713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008389132803656189,"score_gpt":0.2418337022498167,"score_spread":0.2334445694461605,"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."}}