[工程论文]一个通过自动重构优化Java 8流软件的工具

Raffi Khatchadourian, Yiming Tang, M. Bagherzadeh, Syed Ahmed
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引用次数: 11

摘要

流api在主流的面向对象语言和平台中非常普遍。例如,Java 8流API允许在处理有限数据结构(如集合)和无限数据结构时使用类似函数的mapreduce风格的操作。然而,有效地使用此API涉及一些微妙的考虑,例如确定何时并行运行流操作是最好的,何时并行运行操作可能效率较低,以及由于可能的lambda表达式副作用,何时并行运行是安全的。在本文中,我们描述了一个名为Optimize Streams的开源自动重构工具的工程方面,该工具可以帮助开发人员以保持语义的方式编写最佳的流软件。基于新颖的排序和类型状态分析,该工具作为流行的Eclipse IDE的插件实现,同时使用WALA和SAFE框架。我们在11个Java项目中对该工具进行了评估,这些项目包含约64.2万行代码,我们发现36.31%的候选流是可重构的,并且在一个性能套件上平均加速了1.55。我们还描述了从集成三种非常不同的静态分析框架中获得的经验,这些框架为开发人员提供了一个易于使用的界面,用于优化他们的流代码,以充分发挥其潜力。
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[Engineering Paper] A Tool for Optimizing Java 8 Stream Software via Automated Refactoring
Streaming APIs are pervasive in mainstream Object-Oriented languages and platforms. For example, the Java 8 Stream API allows for functional-like, MapReduce-style operations in processing both finite, e.g., collections, and infinite data structures. However, using this API efficiently involves subtle considerations like determining when it is best for stream operations to run in parallel, when running operations in parallel can be less efficient, and when it is safe to run in parallel due to possible lambda expression side-effects. In this paper, we describe the engineering aspects of an open source automated refactoring tool called Optimize Streams that assists developers in writing optimal stream software in a semantics-preserving fashion. Based on a novel ordering and typestate analysis, the tool is implemented as a plug-in to the popular Eclipse IDE, using both the WALA and SAFE frameworks. The tool was evaluated on 11 Java projects consisting of ~642 thousand lines of code, where we found that 36.31% of candidate streams were refactorable, and an average speedup of 1.55 on a performance suite was observed. We also describe experiences gained from integrating three very different static analysis frameworks to provide developers with an easy-to-use interface for optimizing their stream code to its full potential.
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