PDM4AR/exercises
Aug 2025 – Oct 2025
2 Months active
Languages Used
Python
Technical Skills
Algorithm DesignGraph TheorySoftware EngineeringTestingAlgorithm ImplementationBackend Development
Michelangelo Miragoli
PROFILE
Michelangelo Miragoli
Over a two-month period, Mike Miragoli developed and enhanced graph search learning workflows in the PDM4AR/exercises repository, focusing on both feature delivery and code maintainability. He built a ready-to-use template for informed graph search algorithms, including UCS and A*, and refactored data handling and evaluation logic to support modular testing and rapid student iteration. Using Python and applying skills in algorithm design and software engineering, Mike also implemented granular dependency validation and a path-cost utility, converting disallowed dependency checks into a scalable library. His work improved validation fidelity, maintainability, and enabled more reliable assessment of student code submissions.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
2
Lines of code
495
Activity Months2
Your Network
19 peopleSame Organization
@student.ethz.ch13
Work History
October 2025
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for the PDM4AR/exercises repository. Delivered granular dependency validation and a path-cost utility to enable fine-grained control over disallowed dependencies and weighted path analysis. Refactored the validation wrapper to report disallowed library calls precisely, improving exercise validation reliability. Public patch ex03 released as part of this work. This set of changes strengthens validation fidelity, code maintainability, and supports scalable dependency checks across exercises.
2 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for the PDM4AR/exercises repository. Delivered granular dependency validation and a path-cost utility to enable fine-grained control over disallowed dependencies and weighted path analysis. Refactored the validation wrapper to report disallowed library calls precisely, improving exercise validation reliability. Public patch ex03 released as part of this work. This set of changes strengthens validation fidelity, code maintainability, and supports scalable dependency checks across exercises.
October 2025
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, delivered a focused enhancement to the exercises repository to support graph-search learning workflows and robust testing. Implemented a ready-to-use template for Exercise 03 with support for UCS and A* and refined the data handling and evaluation logic to enable quick iteration and accurate assessment of student implementations.
August 2025
1 Commits • 1 Features
Aug 1, 2025In August 2025, delivered a focused enhancement to the exercises repository to support graph-search learning workflows and robust testing. Implemented a ready-to-use template for Exercise 03 with support for UCS and A* and refined the data handling and evaluation logic to enable quick iteration and accurate assessment of student implementations.
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Algorithm DesignAlgorithm ImplementationBackend DevelopmentCode RefactoringCode ValidationGraph TheorySoftware DevelopmentSoftware EngineeringTesting
Repositories Contributed To
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