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1

Obfuscated Clone Search in JavaScript based on Reinforcement Subsequence Learning
Song, Leo ; Ding, Steven H. H. ; Tian, Yuan ; et al.
ACM Transactions on Software Engineering and Methodology. 34(6):1-28

Fachzeitschrift
2

Mutation-Based Deep Learning Framework Testing Method in JavaScript Environment
Zou, Yinglong ; Zhai, Juan ; Fang, Chunrong ; et al.
Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering. :970-981

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3

A Design of Phrase Fill-in-Blank Problem in JavaScript-Based Web-Client Programming Learning Assistant System
Qi, Huiyu ; Li, Zhikang ; Funabiki, Nobuo ; et al.
Proceedings of the 2024 7th International Conference on Computational Intelligence and Intelligent Systems. :146-150

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4

Fuzzing JavaScript Interpreters with Coverage-Guided Reinforcement Learning for LLM-Based Mutation
Eom, Jueon ; Jeong, Seyeon ; Kwon, Taekyoung
Proceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis. :1656-1668

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5

An Empirical Study on the Effects of Obfuscation on Static Machine Learning-Based Malicious JavaScript Detectors
Ren, Kunlun ; Qiang, Weizhong ; Wu, Yueming ; et al.
Proceedings of the 32nd ACM SIGSOFT International Symposium on Software Testing and Analysis. :1420-1432

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6

Towards Understanding the Faults of JavaScript-Based Deep Learning Systems
Quan, Lili ; Guo, Qianyu ; Xie, Xiaofei ; et al.
Proceedings of the 37th IEEE/ACM International Conference on Automated Software Engineering. :1-13

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7

A Combined Model for JavaScript Malicious Code Detection Based on Deep Q-Networks
Wang, Wenming ; Song, Hongru ; Zheng, Jiaolong
Proceedings of the 2025 5th International Conference on Automation Control, Algorithm and Intelligent Bionics. :344-349

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8

Challenging machine learning algorithms in predicting vulnerable JavaScript functions
Ferenc, Rudolf ; Hegedűs, Péter ; Gyimesi, Péter ; et al.
Proceedings of the 7th International Workshop on Realizing Artificial Intelligence Synergies in Software Engineering. :8-14

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9

An Empirical Study of Prioritizing JavaScript Engine Crashes via Machine Learning
Park, Sunnyeo ; Kim, Dohyeok ; Son, Sooel
Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. :646-657

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10

JavaScript Code Suggestion Based on Deep Learning
Zhong, Chaoliang ; Yang, Ming ; Sun, Jun
Proceedings of the 2019 3rd International Conference on Innovation in Artificial Intelligence. :145-149

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11

A Hybrid JavaScript-WebAssembly Framework for Efficient Deep Learning Inference in Web Browsers.
Lee, Chaeeun ; Jeon, Sanghoon
KSII Transactions on Internet & Information Systems. Jan2026, Vol. 20 Issue 1, p243-264. 22p.

Fachzeitschrift
12

PyRHOH: A meta-learning analysis framework for determining the impact of compilation on malicious JavaScript identification
Fulkerson, Eli ; Yocam, Eric ; Vaidyan, Varghese ; et al.
In Machine Learning with Applications August 2025

Fachzeitschrift
14

Accelerating page loads via streamlining JavaScript engine for distributed learning
Liang, Chen ; Wang, Guoyu ; Li, Ning ; et al.
In Information Sciences July 2024 675

Fachzeitschrift
15

Learning JavaScript: a hands-on guide to the fundamentals of modern JavaScript
Learning Java Script

Wright, Tim, 1982- ; Wright, Tim, 1982-

JavaScript (Computer pro... Scripting languages (Com...
Buch
17

Learning JavaScript robotics: design, build, and program your own remarkable robots with JavaScript and open source hardware
Perch, Kassandra, author. ; Perch, Kassandra, author.

Robots -- Programming. Robotics. Arduino (Programmable co... JavaScript (Computer pro...
Buch
18

Learning JavaScript
JavaScript
Learning Java Script

Powers, Shelley. ; Powers, Shelley.

JavaScript (Computer pro...
Buch
19

Learning JavaScript design patterns
Learning Java Script design patterns

Osmani, Addy. ; Osmani, Addy.

JavaScript (Computer pro... Software patterns. Computer software -- Reu... Scripting languages (Com...
Buch
20

Shrinking JavaScript for CS1
Anderson, Boyd ; Henz, Martin ; Low, Kok-Lim ; et al.
Proceedings of the 2021 ACM SIGPLAN International Symposium on SPLASH-E. :87-96

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