Code based grading

Code Grader Implementation Notes

**I. Purpose of the Code Grader**

• The code grader evaluates model output to ensure it meets strict formatting requirements.
• It verifies that the output is only the requested code/data (Python, JSON, or Regular Expression) and contains no explanatory text.
• It checks for valid syntax for the specified output type.

**II. Validation Mechanism**

• Three helper functions are used for syntax validation: validateJSON, validatePython, and validateRegEx.
• Validation Logic:
• The function attempts to parse or compile the model's output.
• Successful parsing/compilation results in a full score of 10.
• Any parsing error results in a score of 0 (failure).
• Format Identification: A general function (grade_syntax) determines which validator to run by checking a format key in the test case dataset.

**III. Implementation Workflow**

• Add Validation Functions: Implement the three helper functions and the general grade_syntax function.
• Update Dataset: Modify the test case dataset to include a format key (e. g. , "JSON", "Python", "RegEx") for each task.
• Refine Prompt Template: Update the prompt to strictly instruct the model to respond only with the required format (JSON, Python, or RegEx) and to omit all commentary or explanation.
• Merge Scores: Integrate the syntax score into the final evaluation.

**IV. Final Scoring**

• The final score is calculated as the average of the Model Score and the Syntax Score.
• Formula: Score = (Model Score + Syntax Score) / 2.

Takeaways

• The code grader ensures model output meets strict formatting requirements, verifying that the response contains only the requested code or data without explanatory text.
• Syntax validation is performed using specific helper functions (e. g. , validateJSON, validatePython, validateRegEx); successful parsing results in a score of 10.
• The implementation workflow requires updating the test dataset to include a format key and refining the prompt to strictly enforce the required output format.
• The final score is calculated as the average of the Model Score and the Syntax Score: Score = (Model Score + Syntax Score) / 2.