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When implementing production software for fixed-point engine control units (ECUs) it is important to consider the code optimization and code verification strategies for the embedded algorithms. System and software engineers work together to design algorithms that satisfy the system performance requirements without significant numerical quantization results. Software engineers and suppliers in mass production environments then implement the design on an embedded system with limited memory and execution speed resources. The primary goals after design are to generate optimized code and verify that the implementation matches the original model’s functional behavior. Model-Based Design simplifies fixed-point development by providing tools and workflows that support the complete design, implementation, and verification processes. System engineers performing on-target rapid prototyping for fixed-point ECUs benefit from automated scaling workflows that provide an initial fixed-point design.

When developing production software for fixed-point Engine Control Units (ECUs), it is important to consider the transition from floating-point to fixed-point algorithms. Systems engineers frequently design algorithms in floating-point math, usually double precision. This represents the ideal algorithm behavior without much concern for its final realization in production software and hardware. Software engineers and suppliers in mass production environments, however, are concerned with production realities and often need to convert these algorithms to fixed-point math for their integer-only hardware. A key task is to design scale factors that maximize code efficiency by minimizing the bytes used, while also minimizing quantization effects such that the fixed-point algorithms match the floating-point results within an acceptable numerical margin.

Software developed for safety-critical systems needs to be of high integrity. Special precautions and development steps are needed for high-integrity software that are not required for other software, although many would argue that they should be. Examples include language subsets, Verification and Validation (V&V), inspections, requirements traceability, documentation, and structural test coverage. Production code generation supports these activities by providing a complete software engineering development environment using models to specify the software. The models can then be tested and stressed within boundaries of the modeling environment. The tests and results can then be reused and applied to the generated code. This paper describes high-integrity code development techniques and shows how they can be automated and applied at the model level, improving quality while shortening design cycles.

When developing software it is important to consider process, methods, and tools. For safety-critical software, standards such as IEC 61508 are often used to impose additional constraints on the development process and require the production of verification evidence and other artifacts. These constraints and artifacts are needed whether or not the design and code were produced manually or via tool automation. This paper discusses the usage of Production Code Generation for safety-critical software development.