WebFuzzing/EvoMaster
May 2025 – Feb 2026
9 Months active
Languages Used
JavaKotlinMarkdownTypeScript
Technical Skills
AI IntegrationAI Model IntegrationAI/MLBackend DevelopmentData ModelingIntegration Testing
Mohsen Taheri Shalmani
PROFILE
Mohsen Taheri Shalmani
Mohsen Taheri developed advanced AI-driven testing and analytics features for the WebFuzzing/EvoMaster repository over nine months, focusing on robust backend systems and maintainable code. He engineered AI model integration, classifier enhancements, and probabilistic evaluation pipelines using Java and Kotlin, enabling more reliable automated test generation and analytics. His work included expanding REST APIs for mathematical utilities, refining input encoding, and implementing neural network and GLM models to improve predictive accuracy. Mohsen prioritized code quality through extensive refactoring, documentation, and test automation, resulting in a more stable, scalable platform that supports rapid iteration, comprehensive evaluation metrics, and streamlined onboarding for contributors.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
112Total
Bugs
5
Commits
112
Features
24
Lines of code
20,156
Activity Months9
Your Network
18 peopleShared Repositories
18
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for WebFuzzing/EvoMaster focusing on test maintainability improvements and stability. Delivered a clarity-driven test class rename and associated updates to the test suite; no major bugs fixed this month; primary gains come from improved maintainability, readability, and onboarding efficiency, which support faster, safer future changes within EvoMaster CI pipelines.
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for WebFuzzing/EvoMaster focusing on test maintainability improvements and stability. Delivered a clarity-driven test class rename and associated updates to the test suite; no major bugs fixed this month; primary gains come from improved maintainability, readability, and onboarding efficiency, which support faster, safer future changes within EvoMaster CI pipelines.
February 2026
January 2026
9 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) — WebFuzzing/EvoMaster delivered two primary AI-centric features that improve observability, reliability, and performance. Features delivered: 1) AI Model Operation Timing and Performance Reporting — Adds timing statistics for update, classification, and repair operations, enabling data-driven performance optimization and SLA tracking. 2) AI Response Classifier: Metrics, Evaluation, and Reliability Enhancements — Expanded metrics tracking, refined evaluation metrics, reliability thresholds, improved failed-case handling, and efficiency optimizations, including reservoir-size reductions in KNN and KDE. Impact: strengthens observability and decision quality for AI-driven flows, reduces latency and memory footprint, and accelerates feedback loops for ongoing model improvements. Demonstrated capabilities include KPI-driven development, performance instrumentation, AI model lifecycle enhancements, and code quality improvements.
January 2026
9 Commits • 2 Features
Jan 1, 2026January 2026 (2026-01) — WebFuzzing/EvoMaster delivered two primary AI-centric features that improve observability, reliability, and performance. Features delivered: 1) AI Model Operation Timing and Performance Reporting — Adds timing statistics for update, classification, and repair operations, enabling data-driven performance optimization and SLA tracking. 2) AI Response Classifier: Metrics, Evaluation, and Reliability Enhancements — Expanded metrics tracking, refined evaluation metrics, reliability thresholds, improved failed-case handling, and efficiency optimizations, including reservoir-size reductions in KNN and KDE. Impact: strengthens observability and decision quality for AI-driven flows, reduces latency and memory footprint, and accelerates feedback loops for ongoing model improvements. Demonstrated capabilities include KPI-driven development, performance instrumentation, AI model lifecycle enhancements, and code quality improvements.
December 2025
16 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for WebFuzzing/EvoMaster focused on strengthening AI-driven decision reliability and update safety. Delivered a consolidated set of enhancements to AI classifier evaluation metrics (with MCC), threshold tuning, and robust update logic across probabilistic endpoint models. Implemented improved handling for invalid inputs and server responses, added configurable behavior for 500 errors, and performed refactors to improve reliability, accuracy, and maintainability of AI-driven decisions and repairs. Completed extensive refactors and tests across AI components, and maintained a disciplined commit trajectory to improve observability and operability in production.
16 Commits • 1 Features
Dec 1, 2025December 2025 monthly summary for WebFuzzing/EvoMaster focused on strengthening AI-driven decision reliability and update safety. Delivered a consolidated set of enhancements to AI classifier evaluation metrics (with MCC), threshold tuning, and robust update logic across probabilistic endpoint models. Implemented improved handling for invalid inputs and server responses, added configurable behavior for 500 errors, and performed refactors to improve reliability, accuracy, and maintainability of AI-driven decisions and repairs. Completed extensive refactors and tests across AI components, and maintained a disciplined commit trajectory to improve observability and operability in production.
December 2025
October 2025
16 Commits • 2 Features
Oct 1, 2025October 2025 — WebFuzzing/EvoMaster: Delivered significant AI-driven improvements and robust input handling to strengthen AI-guided test generation and analytics. Focused on two main feature tracks with an emphasis on reliability, performance, and business value.
October 2025
16 Commits • 2 Features
Oct 1, 2025October 2025 — WebFuzzing/EvoMaster: Delivered significant AI-driven improvements and robust input handling to strengthen AI-guided test generation and analytics. Focused on two main feature tracks with an emphasis on reliability, performance, and business value.
September 2025
34 Commits • 12 Features
Sep 1, 2025September 2025 (2025-09) monthly summary for WebFuzzing/EvoMaster focusing on delivering AI-enabled modeling, expanded ML packing capabilities, and code quality improvements. The month yielded measurable business value through stronger predictive accuracy, broader model packaging support, and a more maintainable codebase, enabling faster feature rollouts and more reliable experimentation.
34 Commits • 12 Features
Sep 1, 2025September 2025 (2025-09) monthly summary for WebFuzzing/EvoMaster focusing on delivering AI-enabled modeling, expanded ML packing capabilities, and code quality improvements. The month yielded measurable business value through stronger predictive accuracy, broader model packaging support, and a more maintainable codebase, enabling faster feature rollouts and more reliable experimentation.
September 2025
August 2025
10 Commits • 2 Features
Aug 1, 2025August 2025 – WebFuzzing/EvoMaster delivered a set of high-impact UX and backend improvements focused on AI-driven evaluation, API expansion, and codebase cleanliness. The work strengthened business value through more reliable AI classifications, richer analytics endpoints, and reduced maintenance overhead.
August 2025
10 Commits • 2 Features
Aug 1, 2025August 2025 – WebFuzzing/EvoMaster delivered a set of high-impact UX and backend improvements focused on AI-driven evaluation, API expansion, and codebase cleanliness. The work strengthened business value through more reliable AI classifications, richer analytics endpoints, and reduced maintenance overhead.
July 2025
1 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for WebFuzzing/EvoMaster: Delivered core API capability and AI model generalization enhancements that broaden cross-API applicability and improve data integrity.
1 Commits • 1 Features
Jul 1, 2025July 2025 performance summary for WebFuzzing/EvoMaster: Delivered core API capability and AI model generalization enhancements that broaden cross-API applicability and improve data integrity.
July 2025
June 2025
20 Commits • 2 Features
Jun 1, 2025June 2025: Delivered meaningful business- and performance-focused enhancements for EvoMaster, combining feature expansion with classifier improvements, while maintaining a strong emphasis on code quality and maintainability. Key outcomes include a new Pet Shop data API suite and enhanced classifier encoding, expanded AI response classification with GLM integration and per-endpoint granularity, and comprehensive documentation/tests with clarified controller naming.
June 2025
20 Commits • 2 Features
Jun 1, 2025June 2025: Delivered meaningful business- and performance-focused enhancements for EvoMaster, combining feature expansion with classifier improvements, while maintaining a strong emphasis on code quality and maintainability. Key outcomes include a new Pet Shop data API suite and enhanced classifier encoding, expanded AI response classification with GLM integration and per-endpoint granularity, and comprehensive documentation/tests with clarified controller naming.
May 2025
5 Commits • 1 Features
May 1, 2025May 2025 monthly summary for WebFuzzing/EvoMaster: delivered robustness improvements and AI capability enhancements with a tight focus on data integrity and testing coverage. Key items: (1) Numeric Endpoint Input Range Validation fixed for /numeric to require x between 1925 and 2025 inclusive, replacing the previous negative-number constraint. Commit: 4d840432fba9b4145e3934fa8f466224452dfc49. (2) Gaussian-based AI Model Enhancements and Testing Framework: added a univariate Gaussian model, enabled doubles at the numeric endpoint, introduced an online classifier with flexible decision making, and established testing utilities and tests. Commits include 4c8936e47dc35c5cdae78a5c43f82b527515129e; d2986d98af9ca4dc053ca908b4b62180a4a06726; efbc6435944b0300a4ecb58752fdd86639c06df9; a605f164802f6a0241d99f79efdd797070dbb733. (3) Expanded testing infrastructure: introduced AICNumericTest.kt updates, NaiveGaussianModel1D, CriteriaChecker, and added testAIModel. (Commits reflected above.) (4) Overall impact: improved data integrity and fuzzing reliability, stronger AI-driven decision making, and broader test coverage, enabling more robust analytics and faster iteration cycles.
5 Commits • 1 Features
May 1, 2025May 2025 monthly summary for WebFuzzing/EvoMaster: delivered robustness improvements and AI capability enhancements with a tight focus on data integrity and testing coverage. Key items: (1) Numeric Endpoint Input Range Validation fixed for /numeric to require x between 1925 and 2025 inclusive, replacing the previous negative-number constraint. Commit: 4d840432fba9b4145e3934fa8f466224452dfc49. (2) Gaussian-based AI Model Enhancements and Testing Framework: added a univariate Gaussian model, enabled doubles at the numeric endpoint, introduced an online classifier with flexible decision making, and established testing utilities and tests. Commits include 4c8936e47dc35c5cdae78a5c43f82b527515129e; d2986d98af9ca4dc053ca908b4b62180a4a06726; efbc6435944b0300a4ecb58752fdd86639c06df9; a605f164802f6a0241d99f79efdd797070dbb733. (3) Expanded testing infrastructure: introduced AICNumericTest.kt updates, NaiveGaussianModel1D, CriteriaChecker, and added testAIModel. (Commits reflected above.) (4) Overall impact: improved data integrity and fuzzing reliability, stronger AI-driven decision making, and broader test coverage, enabling more robust analytics and faster iteration cycles.
May 2025
Activity
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Quality Metrics
Correctness85.4%
Maintainability85.6%
Architecture83.2%
Performance77.0%
AI Usage46.4%
Skills & Technologies
Programming Languages
JavaKotlinMarkdownTypeScript
Technical Skills
AIAI DevelopmentAI IntegrationAI Model ConfigurationAI Model EvaluationAI Model IntegrationAI integrationAI model evaluationAI/MLAI/ML IntegrationAPI AnalysisAPI ClassificationAPI DesignAPI DevelopmentAPI Integration
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