Jacon-ator/4330_Final_Project
Apr 2025 – Jul 2025
3 Months active
Languages Used
C++CMakeDartMarkdown
Technical Skills
Algorithm DesignAlgorithm DevelopmentCode CleanupDartData StructuresData Validation
Aidan Eiler
PROFILE
Aidan Eiler
Eileran developed a foundational Poker Hand Evaluation Engine and Monte Carlo win-probability calculator for the Jacon-ator/4330_Final_Project repository, focusing on robust card and hand modeling, evaluation logic, and test-driven development. Using Dart and Flutter, Eileran designed core data structures and APIs to compare poker hands, including tie-breaker handling and probability calculations. The work included expanding and refactoring the test suite to cover edge cases, improving test clarity, and stabilizing probability-based outcomes. Eileran also enhanced project documentation, streamlining onboarding and reducing ambiguity for contributors. The engineering approach emphasized algorithmic rigor, maintainability, and reliability in game logic and analytics.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
26Total
Bugs
0
Commits
26
Features
5
Lines of code
4,419
Activity Months3
Your Network
9 people
Work History
July 2025
2 Commits • 1 Features
Jul 1, 2025July 2025 focused on documentation quality improvements for the Jacon-ator/4330_Final_Project, enhancing onboarding, readability, and project clarity to support faster feature work and reduced support overhead.
2 Commits • 1 Features
Jul 1, 2025July 2025 focused on documentation quality improvements for the Jacon-ator/4330_Final_Project, enhancing onboarding, readability, and project clarity to support faster feature work and reduced support overhead.
July 2025
May 2025
8 Commits • 2 Features
May 1, 2025Month: 2025-05 — Jacon-ator/4330_Final_Project Concise monthly summary focusing on business value and technical achievements for May 2025. Key features delivered - Poker Hand Evaluation Core Enhancements: introduced a robust _compareRelevantCards and a generic comparePokerHands API to compare two hands with community cards; updated tests to validate tie-breaking outcomes. - Poker Probability and Hand Comparison Test Suite Enhancements: expanded test coverage for top-pair scenarios, unfavorable hand scenarios, flush draws, pocket-pair vs overcards; improved test output formatting and descriptive assertions. Major bugs fixed - Fixed compare cards method to correctly handle tie-breaker scenarios across simulated hands; added tests. - Fixed bug and added tests for set vs flush draw edge case to stabilize probability-based tests. Overall impact and accomplishments - Significantly improved hand evaluation accuracy and reliability in edge cases, increasing correctness of game outcomes and downstream analytics. - Strengthened regression protection through a larger, clearer test suite and better test reporting; reduced ambiguity in test failures. Technologies/skills demonstrated - Algorithm design and refactoring for hand comparison; API design for generic poker hand comparison. - Test-driven development, test suite refactoring, and improved test instrumentation for clearer outcomes. - Edge-case coverage and robustness improvements in a game logic domain.
May 2025
8 Commits • 2 Features
May 1, 2025Month: 2025-05 — Jacon-ator/4330_Final_Project Concise monthly summary focusing on business value and technical achievements for May 2025. Key features delivered - Poker Hand Evaluation Core Enhancements: introduced a robust _compareRelevantCards and a generic comparePokerHands API to compare two hands with community cards; updated tests to validate tie-breaking outcomes. - Poker Probability and Hand Comparison Test Suite Enhancements: expanded test coverage for top-pair scenarios, unfavorable hand scenarios, flush draws, pocket-pair vs overcards; improved test output formatting and descriptive assertions. Major bugs fixed - Fixed compare cards method to correctly handle tie-breaker scenarios across simulated hands; added tests. - Fixed bug and added tests for set vs flush draw edge case to stabilize probability-based tests. Overall impact and accomplishments - Significantly improved hand evaluation accuracy and reliability in edge cases, increasing correctness of game outcomes and downstream analytics. - Strengthened regression protection through a larger, clearer test suite and better test reporting; reduced ambiguity in test failures. Technologies/skills demonstrated - Algorithm design and refactoring for hand comparison; API design for generic poker hand comparison. - Test-driven development, test suite refactoring, and improved test instrumentation for clearer outcomes. - Edge-case coverage and robustness improvements in a game logic domain.
April 2025
16 Commits • 2 Features
Apr 1, 2025April 2025 highlights: Built a foundational Poker Hand Evaluation Engine and Monte Carlo win-probability calculator, with core card/hand models, evaluation logic, and unit tests. Implemented card utilities (class, equality, toString) and hand storage/comparison structures. Developed evaluation scenarios and a prototype probability calculator, with initial tie-handling work in progress. Enhanced documentation and contributor metadata (main.dart and README) to improve onboarding and collaboration. Together, these deliver a solid, test-backed core for odds-based features, enabling more reliable gameplay analytics and faster feature delivery.
16 Commits • 2 Features
Apr 1, 2025April 2025 highlights: Built a foundational Poker Hand Evaluation Engine and Monte Carlo win-probability calculator, with core card/hand models, evaluation logic, and unit tests. Implemented card utilities (class, equality, toString) and hand storage/comparison structures. Developed evaluation scenarios and a prototype probability calculator, with initial tie-handling work in progress. Enhanced documentation and contributor metadata (main.dart and README) to improve onboarding and collaboration. Together, these deliver a solid, test-backed core for odds-based features, enabling more reliable gameplay analytics and faster feature delivery.
April 2025
Activity
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Quality Metrics
Correctness89.6%
Maintainability89.8%
Architecture83.0%
Performance77.8%
AI Usage20.8%
Skills & Technologies
Programming Languages
C++CMakeDartMarkdown
Technical Skills
Algorithm DesignAlgorithm DevelopmentCode CleanupDartData StructuresData ValidationDatabase InteractionDocumentationEnumFactory ConstructorsFlutterFlutter DevelopmentGame DevelopmentGame LogicMonte Carlo Simulation
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