WebFuzzing/EvoMaster
Oct 2025 – Oct 2025
1 Month active
Languages Used
JavaKotlin
Technical Skills
Algorithm DevelopmentAlgorithm TestingCode RefactoringGenetic AlgorithmsObject-Oriented ProgrammingSoftware Design Patterns
francastagna
PROFILE
Francastagna
Worked on the WebFuzzing/EvoMaster repository to enhance the genetic algorithm infrastructure, focusing on maintainability and test coverage. Introduced lifecycle hooks to the AbstractGeneticAlgorithm and refactored MonotonicGeneticAlgorithm to support progress tracking and improved population update logic. Developed comprehensive unit tests for SteadyStateGeneticAlgorithm, covering optimal solution discovery and edge cases such as zero crossover or mutation probabilities. Emphasized test-driven development and code refactoring using Kotlin and Java, while improving documentation and code comments. These efforts resulted in more reliable evolutionary search processes, clearer progress traceability for stakeholders, and a more maintainable codebase for ongoing algorithm development and testing.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
2
Lines of code
585
Activity Months1
Your Network
22 peopleSame Organization
@dc.uba.ar3
Shared Repositories
19
Agustina AldasoroMember
Alexander SzyrejMember
aschenzleMember
arcuri82Member
biboMember
Franco CastagnaMember
fcastagna_meliMember
Philip GarrettMember
Amid GolMember
Work History
October 2025
4 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for WebFuzzing/EvoMaster focused on strengthening genetic algorithm infrastructure and test coverage. Delivered lifecycle-aware MonotonicGeneticAlgorithm and enhanced progress tracking, plus robust SteadyStateGeneticAlgorithm tests and code quality improvements. Result: more reliable evolutionary search, better maintainability, and clearer evidence of progress for stakeholders.
4 Commits • 2 Features
Oct 1, 2025October 2025 performance summary for WebFuzzing/EvoMaster focused on strengthening genetic algorithm infrastructure and test coverage. Delivered lifecycle-aware MonotonicGeneticAlgorithm and enhanced progress tracking, plus robust SteadyStateGeneticAlgorithm tests and code quality improvements. Result: more reliable evolutionary search, better maintainability, and clearer evidence of progress for stakeholders.
October 2025
Activity
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Quality Metrics
Correctness87.4%
Maintainability87.4%
Architecture72.4%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaKotlin
Technical Skills
Algorithm DevelopmentAlgorithm TestingCode RefactoringGenetic AlgorithmsObject-Oriented ProgrammingSoftware Design PatternsSoftware TestingTest-Driven DevelopmentTestingUnit Testing
Repositories Contributed To
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