{"id":"W4387165217","doi":"10.1007/s10270-023-01123-3","title":"Fault localization in DSLTrans model transformations by combining symbolic execution and spectrum-based analysis","year":2023,"lang":"en","type":"article","venue":"Software & Systems Modeling","topic":"Software Testing and Debugging Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Université de Montréal; Polytechnique Montréal","funders":"Agencia Estatal de Investigación; Austrian Science Fund; Bundesministerium für Digitalisierung und Wirtschaftsstandort; Österreichische Nationalstiftung für Forschung, Technologie und Entwicklung; Ministerio de Ciencia e Innovación; Universidad de Málaga","keywords":"Computer science; Symbolic execution; Programming language; Model checking; Parallel computing; Fault (geology); Theoretical computer science; Software engineering; Software","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":[0.0007675617,0.0002119343,0.000354904,0.0009426007,0.0002696053,0.0002511972,0.0003390517,0.0001330467,3.536701e-7],"category_scores_gemma":[0.0001011377,0.0002256127,0.00009141588,0.002719963,0.00002480321,0.000502049,0.00003905714,0.0001730554,0.000003967504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001032757,"about_ca_system_score_gemma":0.00007992813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001003422,"about_ca_topic_score_gemma":0.00004501211,"domain_scores_codex":[0.9981025,0.000104931,0.0005578055,0.0004780648,0.0003682421,0.0003884906],"domain_scores_gemma":[0.9991138,0.0001881499,0.00009947755,0.0004168503,0.00008582881,0.00009590906],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000001943422,0.00001799074,0.003519542,0.0000676873,0.00002109464,0.000002156572,0.001224134,0.9935232,0.0000233384,0.0006734842,0.0002419889,0.0006834512],"study_design_scores_gemma":[0.0002609988,0.00002063804,0.00003131104,0.0001942655,0.00004612351,0.000003289526,0.00004755503,0.9923483,0.00003380891,0.006759646,0.000007728752,0.000246332],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0359574,0.0002344598,0.9539151,0.0001614981,0.00007696651,0.0002796855,0.0000190098,0.009332583,0.00002334473],"genre_scores_gemma":[0.9742458,0.00003305919,0.02538131,0.00008499595,0.0000116574,0.00009143245,0.0001171908,0.00002219767,0.00001238326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9382884,"threshold_uncertainty_score":0.9200218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02208522553743097,"score_gpt":0.2562257732166029,"score_spread":0.2341405476791719,"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."}}