WebFuzzing/EvoMaster
Dec 2024 – Jun 2025
4 Months active
Languages Used
KotlinJavaMarkdownPython
Technical Skills
Algorithm TestingJavaUnit TestingAlgorithm DesignAlgorithm ImplementationCode Readability
Amid Gol
PROFILE
Amid Gol
Over four months, Golmohammadi enhanced the WebFuzzing/EvoMaster repository by developing adaptive input learning models, refining genetic algorithm modules, and improving real-time data visualization. He implemented a Naive Gaussian 1D model in Python and Kotlin to optimize input space exploration, and introduced configurable mutation and monotonic replacement rules to strengthen evolutionary search reliability. His work included comprehensive documentation updates, modular code refactoring, and robust input validation, which improved maintainability and reduced runtime errors. By integrating real-time Kernel Density Estimate plotting and enhancing test automation, Golmohammadi enabled faster experimentation and more reproducible results, demonstrating depth in AI/ML integration and algorithm design.
Overall Statistics
Feature vs Bugs
89%Features
Repository Contributions
16Total
Bugs
1
Commits
16
Features
8
Lines of code
2,924
Activity Months4
Your Network
17 people
Work History
June 2025
5 Commits • 2 Features
Jun 1, 2025June 2025: Enhanced WebFuzzing/EvoMaster with clearer GA documentation, robust input validation and error messaging, and a refactored encoding module. Documentation and status updates improve experiment reproducibility and onboarding; input validation reduces runtime errors; modular encoding improves maintainability and future extensions. Commits across GA docs, classifier validation, and encoding module are traceable to PRs.
5 Commits • 2 Features
Jun 1, 2025June 2025: Enhanced WebFuzzing/EvoMaster with clearer GA documentation, robust input validation and error messaging, and a refactored encoding module. Documentation and status updates improve experiment reproducibility and onboarding; input validation reduces runtime errors; modular encoding improves maintainability and future extensions. Commits across GA docs, classifier validation, and encoding module are traceable to PRs.
June 2025
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 — WebFuzzing/EvoMaster: Key features delivered include adaptive input learning with Naive Gaussian 1D model; genetic algorithms enhancements and documentation; and real-time KDE/result visualization. No major bugs fixed in this period. Overall impact: improved input space exploration, configurable GA options, and real-time observability, enabling faster iteration and data-driven decision making. Technologies demonstrated include Gaussian modeling, evolutionary algorithms, real-time plotting, and documentation improvements.
May 2025
6 Commits • 3 Features
May 1, 2025May 2025 — WebFuzzing/EvoMaster: Key features delivered include adaptive input learning with Naive Gaussian 1D model; genetic algorithms enhancements and documentation; and real-time KDE/result visualization. No major bugs fixed in this period. Overall impact: improved input space exploration, configurable GA options, and real-time observability, enabling faster iteration and data-driven decision making. Technologies demonstrated include Gaussian modeling, evolutionary algorithms, real-time plotting, and documentation improvements.
April 2025
4 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for WebFuzzing/EvoMaster. Focused on improving genetic algorithm readability, maintainability, and core efficiency. Delivered documentation enhancements and core GA improvements that enable faster experimentation and more reliable evolutionary search.
4 Commits • 2 Features
Apr 1, 2025April 2025 monthly summary for WebFuzzing/EvoMaster. Focused on improving genetic algorithm readability, maintainability, and core efficiency. Delivered documentation enhancements and core GA improvements that enable faster experimentation and more reliable evolutionary search.
April 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — WebFuzzing/EvoMaster: Key feature delivery and reliability improvements in GA tests. Achievements include enhancing StandardGeneticAlgorithm Test Validation with updated evaluation configuration, stopping criteria, and new assertions for solution size and fitness, leading to improved accuracy and reduced flaky behavior. No major bugs fixed this month; primary focus was test quality and code robustness. Overall impact includes stronger confidence in GA optimization outcomes, contributing to more reliable fuzzing coverage and product quality. Technologies/skills demonstrated include Java/Kotlin testing, JUnit-like assertions, test configuration tuning, code review, and CI readiness.
December 2024
1 Commits • 1 Features
Dec 1, 2024Month: 2024-12 — WebFuzzing/EvoMaster: Key feature delivery and reliability improvements in GA tests. Achievements include enhancing StandardGeneticAlgorithm Test Validation with updated evaluation configuration, stopping criteria, and new assertions for solution size and fitness, leading to improved accuracy and reduced flaky behavior. No major bugs fixed this month; primary focus was test quality and code robustness. Overall impact includes stronger confidence in GA optimization outcomes, contributing to more reliable fuzzing coverage and product quality. Technologies/skills demonstrated include Java/Kotlin testing, JUnit-like assertions, test configuration tuning, code review, and CI readiness.
Activity
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Quality Metrics
Correctness85.6%
Maintainability87.0%
Architecture77.6%
Performance76.2%
AI Usage25.0%
Skills & Technologies
Programming Languages
JavaKotlinMarkdownPython
Technical Skills
AI/ML IntegrationAI/ML Model DevelopmentAI/ML Model ImplementationAlgorithm DesignAlgorithm ImplementationAlgorithm TestingCSV HandlingCode CleanupCode DocumentationCode OrganizationCode ReadabilityCode RefactoringConfiguration ManagementData ScienceData Visualization
Repositories Contributed To
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