Thank you for participating in this study to evaluate the quality of AI-generated code. Your expertise is crucial in helping us understand the performance of different code generation models.
Your Task: You will be presented with 10 code completion tasks. For each task, you will see:
1. A Code Context, which shows a snippet of code and indicates the position where a completion is needed.
2. The Groud Truth and three anonymous Code Suggestions (A, B, C) generated by different AI models to fill in that position.
Please use the following definitions to score each code suggestion on a scale of 0 to 2.
Criterion 1: Correctness (in context) (Does the completion follow the preceding code in a syntactically and logically valid manner?)
- 0 points: The completion is invalid. It results in a syntax error, a type mismatch, or is complete nonsense in the given context.
- 1 point: The completion is plausible but flawed. It might be syntactically correct but contains a minor logical error or is semantically inconsistent with the context.
- 2 points: The completion is perfectly valid. It is syntactically correct, respects type constraints, and logically follows the program's flow.
Criterion 2: Maintainability (of the suggested code) (Is the suggested code fragment itself clear, idiomatic, and easy to understand?)
(Note that the positions to be completed have been marked as <--- COMPLETION_HERE --->)- 0 points: The suggested code is obfuscated or hard to read. It is unnecessarily complex or uses a confusing style.
- 1 point: The suggested code is functional but could be clearer. It might be slightly convoluted or use non-standard formatting where a better alternative exists.
- 2 points: The suggested code is highly readable and idiomatic. It uses the clearest and most standard way to express the intended logic.