{"id":"W2150898646","doi":"10.1109/iwsess.2009.5068458","title":"MUTEC: Mutation-based testing of Cross Site Scripting","year":2009,"lang":"en","type":"article","venue":"","topic":"Web Application Security Vulnerabilities","field":"Computer Science","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Cross-site scripting; Computer science; JavaScript; Scripting language; Programming language; Set (abstract data type); Test suite; Test script; Test case; Mutation; Web application; Software engineering; Data mining; World Wide Web; Web application security; Web service; Machine learning; Web development","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001497324,0.0008986334,0.0005456695,0.001270388,0.0003160353,0.0005149313,0.001279917,0.0008532205,0.001504979],"category_scores_gemma":[0.007385071,0.0002379879,0.0006167746,0.0004721629,0.000993034,0.001093451,0.0009580576,0.0005896605,0.0002665943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004029008,"about_ca_system_score_gemma":0.000558477,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00121528,"about_ca_topic_score_gemma":0.0007949413,"domain_scores_codex":[0.9978948,0.0005475873,0.000166662,0.0004067758,0.0008147077,0.0001693824],"domain_scores_gemma":[0.9954438,0.002805562,0.0005291909,0.000648531,0.0004637393,0.0001092693],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.001345937,0.0009263469,0.0308982,0.0006467822,0.0002498038,0.002424968,0.0007163013,0.1418428,0.2968861,0.02008264,0.005893637,0.4980864],"study_design_scores_gemma":[0.0001579068,0.0009555142,0.006556334,0.00007698485,0.0000889197,0.001711898,0.0001167644,0.6441528,0.3299159,0.008865378,0.00731272,0.00008893768],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2822778,0.0002013817,0.6863205,0.000201414,0.0000673756,0.0003813887,0.000660777,0.02696472,0.002924746],"genre_scores_gemma":[0.7813179,0.00008975296,0.2149516,0.0001575645,0.00001732775,0.0002712627,0.0008953274,0.0007918149,0.001507483],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001504979,"threshold_uncertainty_score":0.007918715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03075641036596555,"score_gpt":0.2972830597958762,"score_spread":0.2665266494299107,"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."}}