Frank Weil

Model-Driven engineering in a large industrial context — motorola case study

In an ongoing effort to reduce development costs in spite of increasing system complexity, Motorola has been a long-time adopter of Model-Driven Engineering (MDE) practices. The foundation of this approach is the creation of rigorous models throughout the development process, thereby enabling the introduction of automation. In this paper we present our experiences within Motorola in deploying a top-down approach to MDE for more than 15 years. We describe some of the key competencies that have been developed and the impact of MDE within the organization. Next we present some of the main issues encountered during MDE deployment, together with some possible resolutions.

A software environment for parallel computer vision

A software environment tailored to computer vision and image processing (CVIP) that focuses on how information about the CVIP problem domain can make the high-performance algorithms and the sophisticated algorithm techniques being designed by algorithm experts more readily available to CVIP researchers is presented. The environment consists of three principle components: DISC, Cloner, and Graph Matcher. DISC (dynamic intelligent scheduling and control) supports experimentation at the CVIP task level by creating a dynamic schedule from a users specification of the algorithms that constitute a complex task. Cloner is aimed at the algorithm development process and is an interactive system that helps a user design new parallel algorithms by building on and modifying existing library algorithms. Graph Matcher performs the critical step of mapping new algorithms onto the target parallel architecture. Initial implementations of DISC and Graph Matcher have been completed, and work on Cloner is in progress.<<ETX>>

Practical experiences in using model-driven engineering to develop trustworthy computing systems

In this paper, we describe how Motorola has deployed model-driven engineering in product development, in particular for the development of trustworthy and highly reliable telecommunications systems, and outline the benefits obtained. Model-driven engineering has dramatically increased both the quality and the reliability of software developed in our organization, as well as the productivity of our software engineers. Our experience demonstrates that model-driven engineering significantly improves the development process for trustworthy computing systems

Dynamic intelligent scheduling and control of reconfigurable parallel architectures for computer vision/image processing

Abstract This paper presents a system for dynamic intelligent scheduling and control of reconfigurable parallel processors. The purpose of the system is to provide a rapid prototyping capability for computer vision/image processing tasks. The scheduler particularly addresses the problems of algorithms with execution times that depend on the image data and processing scenarios that vary dynamically based on the input image. Since conventional scheduling methods cannot produce schedules for most tasks of this type, a dynamic controller is used to schedule the task and reconfigure the machine “on the fly.” This dynamic scheduling system attempts to balance the overall processing scenario with the needs of the individual routines that make up the task. This paper discusses the implementation of the DISC ( D ynamic I ntelligent S cheduling and C ontrol) system. Emphasis is on the scheduling heuristics as they apply to a reconfigurable parallel processor, the information in the system database, and the use of the system for prototyping computer vision/image processing tasks on a partitionable parallel system.

Experiences in deploying model-driven engineering

In this paper, we describe how Motorola has deployed model-driven engineering in product development, in particular for the development of highly reliable telecommunications systems, and outline the benefits obtained. Model-driven engineering has dramatically increased both the quality and the reliability of software developed in our organization, as well as the productivity of our software engineers. Our experience demonstrates that model-driven engineering significantly improves the development process for telecommunications systems. We discuss the elements we found most important for deployment of model-driven engineering in a large product development organization: An appropriate modeling language, a powerful domain-specific code generator, and a deployment support team.

Formal techniques for automatically generating marshalling code from high-level specifications

This paper presents the application of automated code generation to the development of marshalling code (also known as presentation conversion code). The techniques and automated tools as well as the results of an industrial application are described. Marshalling code amounts to approximately half of the signalling software in subscriber radio, and as such constitutes approximately 20% of the total software in a radio. Development of marshalling code is considered to be a difficult, error-prone, and labor-intensive task. We have successfully developed significant portions of the infrastructure and subscriber software for the TETRA (Terrestrial Trunked Radio) protocol standard through automated code generation techniques using the process outlined in this paper.

Summary of the 2006 model size metrics workshop

A standardized and consistent means of determining the size of an artifact is fundamental to the ability to collect metrics such as defect density and productivity about the artifact. For example, source lines of code is often used as the size metric for C code. However, the concept of lines of code does not readily apply to modeling languages such as UML and SDL. This report summarizes the presentations and discussions on this topic from the 2006 Model Size Metrics workshop.

Automated semantic analysis of design models

Based on several years of experience in generating code from large SDL and UML models in the telecommunications domain, it has become apparent that model analysis must be used to augment more traditional validation and testing techniques. While model correctness is extremely important, the difficulty of use and non-scalability of most formal verification techniques when applied to large-scale design models renders them insufficient for most applications. We have also repeatedly seen that even the most complete test coverage fails to find many problems. In contrast, sophisticated model analysis techniques can be applied without human interaction to large-scale models. A discussion of the model analysis techniques and the model defects that they can detect is provided, along with some real-world examples of defects that have been caught.

Guidelines for using SDL in product development

Over the course of several years working with many diverse projects using SDL for the design of commercial products, we have developed several practical guidelines related to creating SDL models for deployment. This paper discusses the SDL modeling guidelines, covering general recommendations, specific details about using SDL modeling features, performance considerations, platform interface considerations, and portability issues. These guidelines can be used by anyone who is creating design models that will be implemented, either through hand coding or automatic code generation.

Software environment for parallel computer vision

We present a three-part software environment tailored to the areas of computer vision and image processing (CVIP). The environment is designed to provide high performance and ease of use for CVIP researchers implementing algorithms and tasks on parallel systems. Cloner is a software reuse tool that helps a user design parallel algorithms by building on and modifying algorithms from the system library. It takes advantage of the fact that CVIP algorithms are often highly structured and that many algorithms have the same or similar structure. It is being designed as a menu-based, query-based system aimed at reducing the degree to which the user must be concerned with the details of parallel programming. Graph Matcher is a software tool to perform algorithm-to-architecture mapping for image processing algorithms. It consists of a library of known data-dependency structures and of mappings of these structures onto parallel architectures. For the regular graphs that characterize most image processing algorithms, the graph isomorphism used to identify a new algorithm graph as an instance of a library graph is performed in polynomial time. DISC (Dynamic Intelligent Scheduling and Control) is an operating system component that provides a rapid prototyping capability for execution of complex CVIP tasks on partitionable parallel systems. The scheduler addresses the problems of algorithms with execution times that depend on the image data and processing scenarios that vary dynamically based on the input image.