Techniques for Generating and Measuring Production Code Constructs from Controller Models
| Autor: | Bill Chou, Saurabh Mahapatra |
|---|---|
| Rok vydání: | 2009 |
| Předmět: |
Source code
Dead code Computer science media_common.quotation_subject Static program analysis Dead code elimination Object code Computer engineering Control and Systems Engineering Automotive Engineering KPI-driven code analysis Code generation Electrical and Electronic Engineering Safety Risk Reliability and Quality Redundant code media_common |
| Zdroj: | SAE International Journal of Passenger Cars - Electronic and Electrical Systems. 2:27-33 |
| ISSN: | 1946-4622 |
| DOI: | 10.4271/2009-01-0149 |
| Popis: | A key step in Model-Based Design is the deployment of an algorithm as machine code onto a target processor in the production vehicle. Modern software tools automatically generate the algorithmic source code from models. Given the many combinatorial possibilities for realizing a given algorithm within the modeling environment, the generated C source code will be a function of a realization. This dependency is an important consideration because the quality and clarity of the source code impacts the amount of verification and analysis that must be done for production software development. Other factors involved in generating the machine code from the source code, such as compiler optimization and microprocessor architecture, also contribute to this optimization. Organizations that proactively data mine and gather these optimizations into a set of best practices stand to benefit from reduced development times and lower costs. This paper introduces techniques that can be used to generate and measure code constructs used to create a set of best practices for the Simulink modeling environment. The quality of the object code is measured by examining the algorithm compiled within an Integrated Development Environment. |
| Databáze: | OpenAIRE |
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