Towards a Methodology for RTPA-MATLAB Code Generation Based on Machine Learning Rules
James Y. Xu, Yingxu Wang · 2018
Autonomous program code generation by machine learning is not only an ultimate goal but also a theoretical challenge to software science and engineering. A methodology and case study for code generation based on Real-Time Process Algebra (RTPA) by machine learning are presented in this paper. It describes a machine learning approach for code generation in MATLAB based on acquired RTPA rules and formal specifications. The design and implementation of the RTPA-MATLAB code generator is introduced, which is implemented by an RTPA parser and an MATLAB code builder. The experimental case studies have demonstrated the novelty of the theories and methodologies for code generation based on machine-learnt programming rules.