NLP引导的综合：从顺序程序到分布式程序的转变
NLP-Guided Synthesis: Transitioning from Sequential Programs to Distributed Programs
AI总结：
针对顺序代码转分布式代码难度大的问题，提出基于BERT的NLP工具ROOP，可自动将Python代码转为PySpark代码，26个循环片段中成功转换25个，简单操作最短44秒完成，还内置功能等价测试机制。
摘要：
随着大规模数据处理需求的增长，PySpark等分布式编程框架日益普及。然而，将传统顺序代码转换为分布式代码的任务仍是一大障碍，通常需要专业知识和大量时间投入。现有工具虽在自动化转换方面取得进展，但在速度、灵活性和整体适用性上仍有不足。本文提出了ROOP（一种旨在应对这些挑战的突破性工具）来解决上述问题。ROOP利用基于BERT的自然语言处理（NLP）模型，自动将Python代码转换为等效的PySpark代码，为利用分布式计算资源提供了 streamlined 解决方案。我们使用包含26个循环片段的14个不同Python程序对ROOP进行了评估。结果令人鼓舞：ROOP实现了近乎完美的翻译准确率，成功转换了26个循环片段中的25个。值得注意的是，对于更简单的操作，ROOP展现出显著效率，翻译耗时最短仅需44秒。此外，ROOP内置了测试机制，可确保原始代码与翻译后代码的功能等价性，进一步提升了可靠性。本研究为自动化顺序编程向分布式编程的转变开辟了新途径，使开发者能更便捷、高效地完成这一过程。
英文摘要：
As the need for large-scale data processing grows, distributed programming frameworks like PySpark have become increasingly popular. However, the task of converting traditional, sequential code to distributed code remains a significant hurdle, often requiring specialized knowledge and substantial time investment. While existing tools have made strides in automating this conversion, they often fall short in terms of speed, flexibility, and overall applicability. In this paper, we introduce ROOP, a groundbreaking tool designed to address these challenges. Utilizing a BERT-based Natural Language Processing (NLP) model, ROOP automates the translation of Python code to its PySpark equivalent, offering a streamlined solution for leveraging distributed computing resources. We evaluated ROOP using a diverse set of 14 Python programs comprising 26 loop fragments. Our results are promising: ROOP achieved a near-perfect translation accuracy rate, successfully converting 25 out of the 26 loop fragments. Notably, for simpler operations, ROOP demonstrated remarkable efficiency, completing translations in as little as 44 seconds. Moreover, ROOP incorporates a built-in testing mechanism to ensure the functional equivalence of the original and translated code, adding an extra layer of reliability. This research opens up new avenues for automating the transition from sequential to distributed programming, making the process more accessible and efficient for developers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
