可信AI代码生成质量评估数据集

可信AI代码生成质量评估数据集旨在通过多维度指标对AI生成的代码进行系统评估，为开发者、研究人员及产品经理提供一套标准化的质量评估工具。该数据集包含编程语言、代码长度、函数数量、循环数量、条件语句数量、代码复杂度、代码可读性、代码重复率、安全漏洞数量、执行效率、内存使用、AI生成工具、生成时间、质量评分、可信度综合评估等关键参数，全面涵盖代码结构、复杂度、安全性、可读性、效率等多个维度。基于Big-O复杂度分析及基准测试，通过静态分析工具检测漏洞等创新方法，并依托数据聚类算法，显著提升了AI模型生成代码可信度评分的准确性。The Trustworthy AI Code Generation Quality Evaluation Dataset is designed to systematically assess AI-generated code through multi-dimensional metrics, offering a standardized quality assessment toolkit for developers, researchers, and product managers. The dataset comprises key parameters including programming languages, code length, count of functions, count of loops, count of conditional statements, code complexity, code readability, code duplication rate, number of security vulnerabilities, execution efficiency, memory usage, AI generation tools, generation time, quality scores, and comprehensive trustworthiness evaluation, fully covering multiple dimensions such as code structure, complexity, security, readability and efficiency. Leveraging innovative approaches including Big-O complexity analysis, benchmark testing, vulnerability detection via static analysis tools, and data clustering algorithms, the dataset significantly improves the accuracy of trustworthiness scoring for code generated by AI models.

搜集汇总

背景与挑战

背景概述

可信AI代码生成质量评估数据集由连云港锐腾信息科技有限公司开发，旨在通过多维度指标（如代码复杂度、安全性和可读性）系统评估AI生成代码的质量，适用于模型性能评估、企业工具适用性测试、教学培训及AI模型优化等多种场景。该数据集采用Excel格式，利用静态分析和聚类算法提升评估准确性，帮助开发者、研究人员和产品经理标准化评估AI代码生成的可信度。