自动人工智能规划和基于代码模式的代码合成

Jicheng Fu, F. Bastani, I. Yen
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引用次数: 9

摘要

近十年来,嵌入式实时系统的发展取得了长足的进步,在各个应用领域发挥着越来越重要的作用。然而,这些系统越来越复杂,迫切需要开发先进的技术来缩短上市时间和降低整个系统的开发成本。实现这两个目标的一种方法是结合基于组件的软件开发(CBSD)的自动代码合成。这使得合成器能够专注于生成从现有组件组装应用程序所需的粘合代码。主要的挑战是如何使合成器能够识别和生成复杂的条件语句或循环语句。本文对基于模式的代码合成方法进行了改进,使其能够合成新的循环语句。具体来说,我们使用Graphplan的扩展版本来帮助合成器识别和生成新的循环语句。本文提出了一种代码模式规划域模型和代码自动合成系统,该系统将增强型人工智能规划器与代码模式集成系统(CPIS)集成在一起,实现了代码合成过程的完全自动化
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automated AI Planning and Code Pattern Based Code Synthesis
The past decade has seen great progress in the development of embedded real-time systems, which are playing increasingly important roles in various application domains. However, the growing complexity of these systems has revealed the urgent need to develop advanced techniques to reduce the time-to-market as well as the overall system development cost. One method for achieving both of these goals is automated code synthesis combined with component based software development (CBSD). This enables the synthesizer to focus on generating the glue code needed to assemble an application from existing components. The main challenge is how to enable the synthesizer to recognize and generate complex conditional or loop statements. In this paper, a pattern-based code synthesis approach is enhanced to enable it to synthesize new loop statements. Specifically, we use an extended version of Graphplan to help the synthesizer to recognize and generate new loop statements. The paper proposes a planning domain model for code patterns and an automated code synthesis system, which integrates the enhanced AI planner with the code pattern integration system (CPIS) to fully automate the code synthesis process
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