Automatic Algorithm Programming Model Based on the Improved Morgan's Refinement Calculus

Abstract

The automatic algorithm programming model can increase the dependability and efficiency of algorithm program development, including specification generation, program refinement, and formal verification. However, the existing model has two flaws: incompleteness of program refinement and inadequate automation of formal verification. This paper proposes an automatic algorithm programming model based on the improved Morgan's refinement calculus. It extends the Morgan's refinement calculus rules and designs the C++ generation system for realizing the complete process of refinement. Meanwhile, the automation tools VCG (Verification Condition Generator) and Isabelle are used to improve the automation of formal verification. An example of a stock's maximum income demonstrates the effectiveness of the proposed model. Furthermore, the proposed model has some relevance for automatic software generation.