The following Pathfinder Solutions White Papers and User Guides are provided free of charge in PDF format.
Test Driven Development (TDD)
Effective TDD for Complex Embedded Systems
Software development methods allow groups to share techniques that have been found to deliver good results. However, a method that brings success for one team or on a specific class of problem may not work well in a different context until it has been adapted to meet the unique needs of the new context. Test-Driven Development (TDD) is an approach that has been proven to be effective for a broad range of projects- can it work for your team?
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Systems Engineering
Bridging from Systems Engineering to Model Driven Development
Collaboration through Architecture
Key architectural techniques and work products serve as an effective bridge between systems engineering and software development. This paper outlines proven modeling disciplines and other best practices to effectively build this bridge and maintain its long-term health.
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Fundamentals of Systems Modeling
This paper outlines a solid foundation in core modeling skills for systems engineers building complex, high-performance systems with the SysML language. With a focus on modeling fundamentals, this paper outlines how teams can get started with proven techniques. By following a simple step-by-step approach, teams can deliver substantially improved business results like faster time to market, better quality and reduced cost. These proven techniques build a solid start for teams making the shift from ad-hoc diagramming to a more rigorous model-driven approach.
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PI-MDD
Getting the Payoff with MDD
Proven Steps to Get Your Return on Investment
Systems development organizations are under increasing pressure to improve business results. This paper describes not only how these organizations have been changing their expectations in recent years, but also how MDD can resolve issues brought on by these evolving modern-day business practices and philosophies.
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PI-MDD Executive Summary
Platform-Independent Model Drive Development (PI-MDD) is an integrated approach to architecting, developing, testing and deploying complex, high-performance systems software. This paper not only outlines a complete history of the MDD methodology, it describes when it should be used and how it should be adopted.
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MDD for Real-Time and Embedded Systems with PathMATE
This paper describes how by using PI-MDD with PathMATE teams can better achieve higher performance by improving developer productivity, systems quality, and communication, and more effectively manage systems complexity.
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PathMATE Technical Notes
Binary Instance Loading
Binary instance loading provides the most concise data format and best performance for loading and inter-processor transport of large instance populations. Please download the “Binary Instance Loading Tech Note” below for more information.
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Blending Realized Code with PI-MDD Models
Integrating modeled systems with external non-modeled elements is a universal and natural element in building PathMATE systems in real-world settings. There are a wide range of options available in PathMATE to integrate non-modeled C and C++ code, types and components with your PI-MDD modeled systems. Please download the “Blending Realized Code with PI-MDD Models” below for more information.
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Build Generation
PI-MDD modeling allows you to build your system and then deploy it to various target platforms and configurations. Build File Generation provides the automated generation of target environment makefiles or IDE project files. To learn more about makefile and project file generation download the “Build Generation Tech Note” below.
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C Self-Trimming
Automated analysis of the PI-MDD behavior in your model is used to determine which portions of your model aren’t actually accessed at runtime. This feature tailors the generation of code structures and functions for RAM and code space optimization in the PathMATE C-Map implementation architecture. To learn more about target structures and the accessor code for this optimization, download the “UML Foundation for C Self-Trimming Tech Note” below.
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Distributed Deployment
The PI-MDD method for constructing software for complex and high performance systems separates the complexities of the problem space subject matters from the strategies and details of the implementation platforms the system executes within. While programming language and target operating system are key aspects of this implementation platform, they represent one-time selections, often made by organizational inertia.
The distributed deployment of PI-MDD models to multiple execution units is managed with an integrated set of model markings (properties), specialized code generation rules/templates and a flexible set of implementation mechanisms. The PI-MDD models remain independent of this target environment topology, and can be deployed to a range of topologies to support unit testing, system testing, and alternative deployment architectures. To learn more about the distributed deployment of PI-MDD models to multiple execution units, download the “Distributed Deployment Tech Note” below.
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Index-Based Instance Identification
Index-based instance identification allows for the efficient retrieval of object instances from an instance population. Index-based instance identification affects several areas of the design including:
- » How instances plug themselves into the instance population set.
- » How WHERE clauses are processed when the index attribute is specified in the clause
- » How instances unplug themselves from the instance population
To learn more about the implementation of this feature, download the “Index-Based Instance Identification Tech Note” below.
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Multi-Process Message Formats
This Technical Note describes the Message formats used in PathMATE Multi-Process deployments when communicating between any two process instances. This includes an overview of the different message protocol layers involved during transmission defining basic terminology and the basic concepts, and the PathMATE Application Messaging Protocol and all supported message formats.
To learn more about interprocess message formats, download the “Index-Based Instance Identification Tech Note” below.
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Specialized Memory Pool for C and C++
To improve static buffer management for intertask deployments, extensions to PathMATE’s C and C++ Maps support task-local memory management pools and are based on the buffer manager. To learn more about these task specific pools and extensions, download the Specialized Memory Pool for C and C++ Tech Note below.
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PathMATE Transformation Maps Mutex Controls
In order to safely deploy a single domain to multiple tasks, key model markings are used to generate intertask mutual exclusion (“mutex”) control mechanisms. The domain IntertaskMutex property specifies what mutex control(s) may be applied as required by IntertaskProtect settings. To learn more about mutex controls and their functionality, download the “PathMATE Transformation Maps Mutex Controls Tech Note” below.
