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All sourcesNASA NTRSDOE OSTI
NASA NTRS1998

Incorporating Manual and Autonomous Code Generation

Code can be generated manually or using code-generated software tools, but how do you interpret the two? This article looks at a design methodology that combines object-oriented design with autonomic code generation for attitude control flight software. Recent improvements in space flight computers are allowing software engineers to spend more time engineering the applications software. The application developed was the attitude control flight software for an astronomical satellite called the Microwave Anisotropy Probe (MAP). The MAP flight system is being designed, developed, and integrated at NASA's Goddard Space Flight Center. The MAP controls engineers are using Integrated Systems Inc.'s MATRIXx for their controls analysis. In addition to providing a graphical analysis for an environment, MATRIXx includes an autonomic code generation facility called AutoCode. This article examines the forces that shaped the final design and describes three highlights of the design process: (1) Defining the manual to autonomic code interface; (2) Applying object-oriented design to the manual flight code; (3) Implementing the object-oriented design in C.

McComas, David↗
NASA NTRS1993

Evaluation of the efficiency and fault density of software generated by code generators

Flight computers and flight software are used for GN&C (guidance, navigation, and control), engine controllers, and avionics during missions. The software development requires the generation of a considerable amount of code. The engineers who generate the code make mistakes and the generation of a large body of code with high reliability requires considerable time. Computer-aided software engineering (CASE) tools are available which generates code automatically with inputs through graphical interfaces. These tools are referred to as code generators. In theory, code generators could write highly reliable code quickly and inexpensively. The various code generators offer different levels of reliability checking. Some check only the finished product while some allow checking of individual modules and combined sets of modules as well. Considering NASA's requirement for reliability, an in house manually generated code is needed. Furthermore, automatically generated code is reputed to be as efficient as the best manually generated code when executed. In house verification is warranted.

Schreur, Barbara↗
NASA NTRS1994

Evaluation of the efficiency and reliability of software generated by code generators

There are numerous studies which show that CASE Tools greatly facilitate software development. As a result of these advantages, an increasing amount of software development is done with CASE Tools. As more software engineers become proficient with these tools, their experience and feedback lead to further development with the tools themselves. What has not been widely studied, however, is the reliability and efficiency of the actual code produced by the CASE Tools. This investigation considered these matters. Three segments of code generated by MATRIXx, one of many commercially available CASE Tools, were chosen for analysis: ETOFLIGHT, a portion of the Earth to Orbit Flight software, and ECLSS and PFMC, modules for Environmental Control and Life Support System and Pump Fan Motor Control, respectively.

Schreur, Barbara↗
NASA NTRS2023

Utilizing Code Generation from Models for Electric Aircraft Motor Controller Flight Software

The processes followed to develop and test safety-critical flight software significantly increase development effort and overhead in comparison to both non-safety-critical and non-flight software. Generating code from models can be used to reduce development effort; however, the processes for using code generation to develop flight software are relatively immature. This work presents an approach for developing safety-critical flight software utilizing code generation from models to reduce development time and effort. The presented use-case is of electric aircraft motor control software developed for NASA's X-57 Maxwell aircraft.

flight software↗
NASA NTRS2012

Auto Code Generation for Simulink-Based Attitude Determination Control System

This paper details the work done to auto generate C code from a Simulink-Based Attitude Determination Control System (ADCS) to be used in target platforms. NASA Marshall Engineers have developed an ADCS Simulink simulation to be used as a component for the flight software of a satellite. This generated code can be used for carrying out Hardware in the loop testing of components for a satellite in a convenient manner with easily tunable parameters. Due to the nature of the embedded hardware components such as microcontrollers, this simulation code cannot be used directly, as it is, on the target platform and must first be converted into C code; this process is known as auto code generation. In order to generate C code from this simulation; it must be modified to follow specific standards set in place by the auto code generation process. Some of these modifications include changing certain simulation models into their atomic representations which can bring new complications into the simulation. The execution order of these models can change based on these modifications. Great care must be taken in order to maintain a working simulation that can also be used for auto code generation. After modifying the ADCS simulation for the auto code generation process, it is shown that the difference between the output data of the former and that of the latter is between acceptable bounds. Thus, it can be said that the process is a success since all the output requirements are met. Based on these results, it can be argued that this generated C code can be effectively used by any desired platform as long as it follows the specific memory requirements established in the Simulink Model.

MolinaFraticelli, Jose Carlos↗
NASA NTRS2009

Generating Code Review Documentation for Auto-Generated Mission-Critical Software

Model-based design and automated code generation are increasingly used at NASA to produce actual flight code, particularly in the Guidance, Navigation, and Control domain. However, since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently auto-generated code still needs to be fully tested and certified. We have thus developed AUTOCERT, a generator-independent plug-in that supports the certification of auto-generated code. AUTOCERT takes a set of mission safety requirements, and formally verifies that the autogenerated code satisfies these requirements. It generates a natural language report that explains why and how the code complies with the specified requirements. The report is hyper-linked to both the program and the verification conditions and thus provides a high-level structured argument containing tracing information for use in code reviews.

Denney, Ewen↗
NASA NTRS1985

Users manual for coordinate generation code CRDSRA

Generation of a viable coordinate system represents an important component of an isolated airfoil Navier-Stokes calculation. The manual describes a computer code for generation of such a coordinate system. The coordinate system is a general nonorthogonal one in which high resolution normal to the airfoil is obtained in the vicinity of the airfoil surface, and high resolution along the airfoil surface is obtained in the vicinity of the airfoil leading edge. The method of generation is a constructive technique which leads to a C type coordinate grid. The method of construction as well as input and output definitions are contained herein. The computer code itself as well as a sample output is being submitted to COSMIC.

Shamroth, S. J.↗
NASA NTRS1992

IGB grid: User's manual (A turbomachinery grid generation code)

A grid generation code called IGB is presented for use in computational investigations of turbomachinery flowfields. It contains a combination of algebraic and elliptic techniques coded for use on an interactive graphics workstation. The instructions for use and a test case are included.

Beach, T. A.↗
NASA NTRS2008

Automatic Code Generation for Instrument Flight Software

Automatic code generation can be used to convert software state diagrams into executable code, enabling a model- based approach to software design and development. The primary benefits of this process are reduced development time and continuous consistency between the system design (statechart) and its implementation. We used model-based design and code generation to produce software for the Electra UHF radios that is functionally equivalent to software that will be used by the Mars Reconnaissance Orbiter (MRO) and the Mars Science Laboratory to communicate with each other. The resulting software passed all of the relevant MRO flight software tests, and the project provides a useful case study for future work in model-based software development for flight software systems.

state charts↗
NASA NTRS2006

ESAS Deliverable PS 1.1.2.3: Customer Survey on Code Generations in Safety-Critical Applications

Automated code generators (ACG) are tools that convert a (higher-level) model of a software (sub-)system into executable code without the necessity for a developer to actually implement the code. Although both commercially supported and in-house tools have been used in many industrial applications, little data exists on how these tools are used in safety-critical domains (e.g., spacecraft, aircraft, automotive, nuclear). The aims of the survey, therefore, were threefold: 1) to determine if code generation is primarily used as a tool for prototyping, including design exploration and simulation, or for fiight/production code; 2) to determine the verification issues with code generators relating, in particular, to qualification and certification in safety-critical domains; and 3) to determine perceived gaps in functionality of existing tools.

Schumann, Johann↗
NASA NTRS2009

Deriving Safety Cases for the Formal Safety Certification of Automatically Generated Code

We present an approach to systematically derive safety cases for automatically generated code from information collected during a formal, Hoare-style safety certification of the code. This safety case makes explicit the formal and informal reasoning principles, and reveals the top-level assumptions and external dependencies that must be taken into account; however, the evidence still comes from the formal safety proofs. It uses a generic goal-based argument that is instantiated with respect to the certified safety property (i.e., safety claims) and the program. This will be combined with a complementary safety case that argues the safety of the framework itself, in particular the correctness of the Hoare rules with respect to the safety property and the trustworthiness of the certification system and its individual components. Keywords: Automated code generation, Hoare logic, formal code certification, safety case, Goal Structuring Notation.

Basir, Nurlida↗
DOE OSTI2025

Code Generators for Floating-Point Unit Design in Integrated Circuits (OpenFloat) v1.0

This IP provides a comprehensive set of code generators for various floating-point units (FPUs) essential for integrated circuit design and integration, targeting a broad spectrum of applications, including machine learning and scientific computing. The suite includes FP adders, multipliers, subtractors, dividers, reciprocals, exponentials, square roots, trigonometric functions (sine, cosine, arctangent), and more. It supports customizable hardware design parameters, such as precision (16, 32, 64, and 128 bits) and pipeline depths, offering users enhanced flexibility and productivity. The generated code is in an industry-standard hardware description language, ensuring compatibility with standard design flows, including simulation, verification, synthesis, and implementation on both field-programmable gate arrays (FPGAs) and application-specific integrated circuits (ASICs).

Shalf, JohnM. [Lawrence Berkeley National Laborato↗
NASA NTRS2009

Modeling Guidelines for Code Generation in the Railway Signaling Context

Modeling guidelines constitute one of the fundamental cornerstones for Model Based Development. Their relevance is essential when dealing with code generation in the safety-critical domain. This article presents the experience of a railway signaling systems manufacturer on this issue. Introduction of Model-Based Development (MBD) and code generation in the industrial safety-critical sector created a crucial paradigm shift in the development process of dependable systems. While traditional software development focuses on the code, with MBD practices the focus shifts to model abstractions. The change has fundamental implications for safety-critical systems, which still need to guarantee a high degree of confidence also at code level. Usage of the Simulink/Stateflow platform for modeling, which is a de facto standard in control software development, does not ensure by itself production of high-quality dependable code. This issue has been addressed by companies through the definition of modeling rules imposing restrictions on the usage of design tools components, in order to enable production of qualified code. The MAAB Control Algorithm Modeling Guidelines (MathWorks Automotive Advisory Board)[3] is a well established set of publicly available rules for modeling with Simulink/Stateflow. This set of recommendations has been developed by a group of OEMs and suppliers of the automotive sector with the objective of enforcing and easing the usage of the MathWorks tools within the automotive industry. The guidelines have been published in 2001 and afterwords revisited in 2007 in order to integrate some additional rules developed by the Japanese division of MAAB [5]. The scope of the current edition of the guidelines ranges from model maintainability and readability to code generation issues. The rules are conceived as a reference baseline and therefore they need to be tailored to comply with the characteristics of each industrial context. Customization of these recommendations has been performed for the automotive control systems domain in order to enforce code generation [7]. The MAAB guidelines have been found profitable also in the aerospace/avionics sector [1] and they have been adopted by the MathWorks Aerospace Leadership Council (MALC). General Electric Transportation Systems (GETS) is a well known railway signaling systems manufacturer leading in Automatic Train Protection (ATP) systems technology. Inside an effort of adopting formal methods within its own development process, GETS decided to introduce system modeling by means of the MathWorks tools [2], and in 2008 chose to move to code generation. This article reports the experience performed by GETS in developing its own modeling standard through customizing the MAAB rules for the railway signaling domain and shows the result of this experience with a successful product development story.

Ferrari, Alessio↗
NASA NTRS2005

Automatic Certification of Kalman Filters for Reliable Code Generation

AUTOFILTER is a tool for automatically deriving Kalman filter code from high-level declarative specifications of state estimation problems. It can generate code with a range of algorithmic characteristics and for several target platforms. The tool has been designed with reliability of the generated code in mind and is able to automatically certify that the code it generates is free from various error classes. Since documentation is an important part of software assurance, AUTOFILTER can also automatically generate various human-readable documents, containing both design and safety related information. We discuss how these features address software assurance standards such as DO-178B.

Denney, Ewen↗
NASA NTRS1984

New GOES satellite synchronized time code generation

The TRAK Systems' GOES Satellite Synchronized Time Code Generator is described. TRAK Systems has developed this timing instrument to supply improved accuracy over most existing GOES receiver clocks. A classical time code generator is integrated with a GOES receiver.

Fossler, D. E.↗