@phdthesis{digilib78063,
           month = {June},
           title = {RANCANG BANGUN EKSTENSI VISUAL STUDIO CODE UNTUK DETEKSI BUG JAVASCRIPT BERBASIS RULE-BASED STATIC ANALYSIS},
          school = {UIN SUNAN KALIJAGA YOGYAKARTA},
          author = {NIM.: 22106050020 Rafi Alaudin Al Hafidz},
            year = {2026},
            note = {Dr. Agus Mulyanto, S.Si., M.Kom., ASEAN Eng.},
        keywords = {JavaScript; Visual Studio Code; Rule-Based Static Analysis; AST; bug detection.},
             url = {https://digilib.uin-suka.ac.id/id/eprint/78063/},
        abstract = {This research discusses the design and development of a Visual Studio Code extension for detecting potential bugs in JavaScript code using Rule-Based Static Analysis. The main problem addressed is the delayed detection of bugs during the coding process, particularly issues related to improper operator usage, remaining debugging statements, risky function usage, and poor coding practices.
The development method used in this research is Design and Development (D\&D), which consists of analysis, design, development, and evaluation stages. The system works by reading JavaScript code, parsing it into an Abstract Syntax Tree (AST), analyzing it through a rule engine, and displaying the detection results using the Diagnostic API in the Visual Studio Code editor.
Testing was conducted through black box testing, rule testing on 15 JavaScript bug detection rules, additional testing on 10 JavaScript files from public code examples referring to ESLint Rules documentation, and User Acceptance Testing (UAT) involving 10 respondents. The tested rules include no-assignment-in-if, use-eq-eq-eq, use-isnan, no-console-log, no-debugger, no-self-assign, no-empty-block, no-constant-condition, no-math-object-call, no-alert, no-template-curly-in-string, no-throw-literal, no-nested-ternary, no-eval, and no-implied-eval. The rule selection was adapted from error patterns documented in JavaScript code analysis tools such as ESLint and JSHint, then adjusted to the scope of this research. The results show that all rules successfully detected the expected error patterns, achieving a rule detection success rate of 100\%. The UAT result obtained an average score of 4.53 out of 5, categorized as strongly agree. Therefore, the developed extension can be used as an early detection tool for potential JavaScript bugs in the Visual Studio Code editor.}
}