Automated AI Planning and Code Pattern Based Code Synthesis

Abstract

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.