Initial MiniGrades v1 and v2 specs, tests and problem config - #9
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- Added solution.py and 15 automated pytest cases in test.py. - Integrated SPEC.txt to define the core technical requirements. - Note: Initial version follows a linear logic (no loops/lists) as a stable testing baseline. - Compliance: All output formats and error handling strictly follow SPEC.txt.
- Created SPEC.txt for the baseline version of MiniGrades with core commands: init, add, add-grade, list, delete, and report. - Developed solution.py as a functional baseline implementation focusing on direct file I/O and strict specification compliance. - Integrated test.py featuring 15 automated pytest cases to validate core student/grade management and edge-case handling. - Note: Initial implementation follows a linear logic (no loops/lists) to establish a stable and verifiable testing foundation.
Updated project specifications for mini-grades to version 1, adding new functions and improving error handling.
Refactored minigrades (v1) implementation to support loops and lists for dynamic data management. Added persistent storage for grades and real-time average calculation, along with improved error handling.
Migrated the testing framework to align with v1 system architecture, moving from basic string matching to structured data validation.
berkevnl
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the miniplaylist dir MUST contain only
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Okay, I will add necessary files. |
berkevnl
changed the title
Added MiniGrades problem and edited descriptions in README.md.
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I added necessary files and revised README.md with new problem. |
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🚀 Overview
This PR introduces the core infrastructure for the
minigradesproblem within the benchmark suite. It establishes a clear evolution from a stateless grading script (v1) to a persistent, data-driven system (v2), enabling comprehensive testing of AI agents' ability to handle state and file I/O operations.💻 What is MiniGrades ?
Mini-grades is a simple command-line interface (CLI) tool designed to manage student records and track academic performance.
🔄 Changelog for MiniGrades (v1 to v2)
📂 Changes & Additions
problem.json: Defined the benchmark entry point, mapping the specifications and test suites for the runner engine.spec_v1.txt&spec_v2.txt: Detailed technical requirements for AI agents.test_v1.sh&test_v2.sh: Automated verification scripts to validate the correctness, edge-case handling, and storage integrity of the generated solutions.⚙️ Technical Focus
which-languageruntime, ensuring cross-platform compatibility (handling CRLF/LF transitions).