five

DrAsync: Identifying and Visualizing Anti-Patterns inAsynchronous JavaScript [Anonymous Experimental Data]

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NIAID Data Ecosystem2026-03-12 收录
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https://zenodo.org/record/5428997
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//////////////////////////////////// // This directory contains the raw data used to compute aggregate numbers in the paper. There are five files, and 2 subdirectories: (1) apply_run_times: has the raw execution times of various calls to apply throughout vuepress' tests; (2) cpdir_run_times: has the raw execution times of calling cpDir on a large directory as part of the cpDir case study; (3) eleventy_test_executions: contains 50 run times x 2 (before, after refactoring) for eleventy's test suite; (4) promise_resolve_then_case_study: contains execution times for the code fragment from strapi's evaluate function; (5) vuepress_test_executions: contains 50 run times x 2 (before, after refactoring) for vuepress' test suite. For the subdirectories: (1) DynamicAndExecutedAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number                                     of static occurences of anti-patterns which are executed, as well as how often. (2) StaticAntiPatterns: for each of 20 subject applications x for each of 8 anti-patterns, contains the number of static                         occurrences of the anti-pattern. We further filtered this by discounting anti-patterns appearing                         in test, generated, build, etc. directories with a separate command. //////////////////////////////////// // CodeQL queries for the anti-patterns are given in supplemental material (available on the submission form).  We will make the code for the visualization tool available as part of the artifact submission process if this paper is accepted.
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2021-09-04
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