Analysis and Optimization of Object-Oriented Languages

面向对象语言的分析与优化

• 批准号: 9503741
• 负责人: Craig Chambers
• 金额: $ 14.99万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1995
• 资助国家: 美国
• 起止时间: 1995-09-15 至 1999-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9503741&HistoricalAwards=false
• 关键词: Analysis; Optimization; Object; Oriented; Languages

Object-oriented languages offer one promising approach to making programs easier to write and easier to modify and extend. Unfortunately, object-oriented language constructs often incur a substantial run-time cost. To improve the run-time performance of object-oriented languages, previous research applied intraprocedural class analysis and compile-time class prediction to determine the actual classes of arguments to a dynamically bound call at compile-time, thereby statically binding the call to the target procedure and enabling inline expansion to eliminate the overhead of the call. This work was performed primarily in the context of purely object-oriented languages. The goal of this project is to extend previous work in three directions. First, the scope of analysis will be expanded to the whole application program. This necessitates developing and evaluating techniques for constructing call graphs for object-oriented languages and performing interprocedural class analysis. Second, profile information will be incorporated into the analysis and optimization process. In particular, profile information can provide much more accurate class prediction information than can static estimation techniques. Third, procedure specialization will be selectively applied to the optimization of object-oriented languages. The goal will be to investigate the relative trade-offs in cost and benefit among inline expansion, procedure specialization, and interprocedural analysis for object-oriented languages. The suitability of these techniques across a range of object-oriented programming languages, both pure and hybrid, will be evaluated in this effort.

面向对象语言提供了一种有前途的方法，使程序更易于编写、修改和扩展。不幸的是，面向对象的语言构造通常会产生大量的运行时成本。为了提高面向对象语言的运行时性能，先前的研究应用过程内类分析和编译时类预测来确定编译时动态绑定调用的实际参数类，从而将调用静态绑定到目标过程并启用内联扩展以消除调用的开销。 这项工作主要是在纯面向对象语言的背景下进行的。该项目的目标是在三个方向上扩展之前的工作。首先，将分析范围扩大到整个应用程序。这就需要开发和评估用于构建面向对象语言的调用图和执行过程间类分析的技术。 其次，档案信息将纳入分析和优化过程。特别是，概况信息可以提供比静态估计技术更准确的类别预测信息。 第三，过程专业化将有选择地应用于面向对象语言的优化。目标是研究面向对象语言的内联扩展、过程专业化和过程间分析之间的成本和收益的相对权衡。这项工作将评估这些技术在一系列面向对象编程语言（纯语言和混合语言）中的适用性。