Programming Benchmarks

Programming benchmarks evaluate LLMs’ ability to write, debug, and understand code across various programming languages and problem domains. These benchmarks test coding skills, algorithmic thinking, and software development capabilities.

Overview

These benchmarks assess how well LLMs can:

  • Generate functional code from specifications

  • Debug and fix existing code

  • Understand and explain code functionality

  • Solve algorithmic problems

  • Work with multiple programming languages

  • Follow coding best practices and standards

Key Benchmarks

HumanEval

Purpose: Evaluates code generation capabilities through function completion tasks

Description: HumanEval presents LLMs with function signatures and docstrings, asking them to complete the function implementation. The benchmark tests the model’s ability to understand requirements and generate working code.

Resources: HumanEval dataset | HumanEval Paper

MBPP (Mostly Basic Python Programming)

Purpose: Tests basic Python programming skills and problem-solving abilities

Description: MBPP consists of 974 programming problems that test fundamental Python concepts, data structures, and algorithms. The benchmark evaluates both code correctness and solution efficiency.

Resources: MBPP dataset | MBPP Paper

CodeContests

Purpose: Evaluates competitive programming and algorithmic problem-solving skills

Description: CodeContests presents programming challenges similar to those found in competitive programming competitions. The benchmark test an LLM’s ability to solve complex algorithmic problems efficiently.

Resources: CodeContests dataset | CodeContests Paper

Coding tasks are also included in other benchmarks such as BigBench, which covers various reasoning types including programming and algorithmic problem-solving.