Model based code generation for distributed embedded systems

Embedded systems are becoming increasingly complex and more distributed. Cost and quality requirements necessitate reuse of the functional software components for multiple deployment architectures. An important step is the allocation of software components to hardware. During this process the differences between the hardware and application software architectures must be reconciled. In this paper we discuss an architecture driven approach involving model-based techniques to resolve these differences and integrate hardware and software components. The system architecture serves as the underpinning based on which distributed real-time components can be generated. Generation of various embedded system architectures using the same functional architecture is discussed. The approach leverages the following technologies – IME (Integrated Modeling Environment), the SAE AADL (Architecture Analysis and Design Language), and Ocarina. The approach is illustrated using the electronic throttle control system as a case study

Cloud Architecture Evaluation

Cloud computing has introduced numerous ways to build software systems in the cloud environment. The complexity of today’s system architectures require architecture evaluation in the designing phase of the system, in the implementation phase, and in the maintenance phase. There are many different architecture evaluation models. This thesis discusses three different evaluation models: architecture tradeoff analysis method, cost-benefit analysis method, and AWS Well-Architected framework. The AWS Well-Architected framework is deeply evaluated by performing an architectural evaluation for the case study software: Lixani 5. This thesis introduces and compares the opportunities for cloud architecture evaluation by literature review, case study, and interviews with experts. The thesis begins with introduction to cloud computing, cloud architecture models and architecture evaluation methods. An architecture evaluation for a case study software is then carried out. This thesis also contains interviews with experts, producing knowledge on how the system architecture is being evaluated in the field. The research methods used in the thesis are literature review, case study, and expert interviews. This thesis attempts to describe and assess the architecture evaluation models by using the research methods. In addition, this thesis introduces and discusses the case study software – Lixani 5 – and its architectural decisions. Based on research in the thesis it was noted that all three studied software architecture evaluation models are suitable options for reviewing software architecture. All models included positive and negative aspects and none of them was seen as superior compared to the others. Based on the interviews with experts it was noted that there are also multiple other efficient ways to evaluate the system architecture than the models discussed in the thesis. These ways included a technology audit template and a proof-of-concept culture

A Large-Scale Industrial Case Study on Architecture-Based Software Reliability Analysis

Abstract—Architecture-based software reliability analysis methods shall help software architects to identify critical software components and to quantify their influence on the system reliability. Although researchers have proposed more than 20 methods in this area, empirical case studies applying these methods on large-scale industrial systems are rare. The costs and benefits of these methods remain unknown. On this behalf, we have applied the Cheung method on the software architecture of an industrial control system from ABB consisting of more than 100 components organized in nine subsystems with more than three million lines of code. We used the Littlewood/Verrall model to estimate subsystems failure rates and logging data to derive subsystem transition probabilities. We constructed a discrete time Markov chain as an architectural model and conducted a sensitivity analysis. This paper summarizes our experiences and lessons learned. We found that architecture-based software reliability analysis is still difficult to apply and that more effective data collection techniques are required. Keywords-Software reliability growth, software architecture, Markov processes I

A DIGITAL ENGINEERING CASE STUDY OF AN UNMANNED UNDERWATER VEHICLE

Team Icarus created a digital engineering case study based on an unmanned underwater vehicle (UUV) to provide a robust view of developing an architecture using Cameo Systems Modeler by executing the MagicGrid architecture development methodology. The case study includes connecting this architecture model to directly drive several engineering analysis tools (Excel, MATLAB/Simulink, a Computer Aided Design tool) through middle-ware software (ModelCenter MBSE). The design was refined through a design of experiments and is visualized through software tools (ModelCenter Explore). This case study is provided to Naval Surface Warfare Center–Port Hueneme Division (NSWC PHD) to be a supplement to the training of systems engineers and systems logisticians to fill in the gaps of existing trainings. This case study is also provided to Naval Postgraduate School to supplement the education of current and future students on architecture development and digital engineering.Civilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyCivilian, Department of the NavyApproved for public release. Distribution is unlimited

Towards a broader view on software architecture analysis of flexibility

Software architecture analysis helps us assess the quality of a software system at an early stage. In this paper we describe a case study of software architecture analysis that we have performed to assess the flexibility of a large administrative system. Our analysis was based on scenarios, representing possible changes to the requirements of the system and its environment. Assessing the effect of these scenarios provides insight into the flexibility of the system. One of the problems is to express the effect of a scenario in such a way that it provides insight into the complexity of the necessary changes. Part of our research is directed at developing an instrument for doing just that. This instrument is applied in the analysis described in this paper

About Designing an Observer Pattern-Based Architecture for a Multi-objective Metaheuristic Optimization Framework

Multi-objective optimization with metaheuristics is an active and popular research field which is supported by the availability of software frameworks providing algorithms, benchmark problems, quality indicators and other related components. Most of these tools follow a monolithic architecture that frequently leads to a lack of flexibility when a user intends to add new features to the included algorithms. In this paper, we explore a different approach by designing a component-based architecture for a multi-objective optimization framework based on the observer pattern. In this architecture, most of the algorithmic components are observable entities that naturally allows to register a number of observers. This way, a metaheuristic is composed of a set of observable and observer elements, which can be easily extended without requiring to modify the algorithm. We have developed a prototype of this architecture and implemented the NSGA-II evolutionary algorithm on top of it as a case study. Our analysis confirms the improvement of flexibility using this architecture, pointing out the requirements it imposes and how performance is affected when adopting it.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

BIM + Sustainability: Case Study on IES VE Building Performance Simulation

The D.Arch project I have chosen is a case study of the IES (Integrated Environmental Solutions Virtual Environment) Software. The objective of this case study is to challenge the software’s modules capabilities i.e. Radiance, Suncast, and Apache SIM, in conjunction with the Revit MEP (Mechanical, Electrical, and Plumbing) Modeling software. Revit MEP is a building information modeling software developed by Autodesk. The other component to the D.Arch Project is an entry into an Architecture Student competition called Leading Edge 2007/2008. Leading Edge Student Competition 2007/2008 is sponsored by UCSB (University of California Santa Barbara). I chose this competition because building performance analysis is a requirement. I will select a base-case building that has satisfactory energy efficiency standards. I will then compare my design to the base case model. I will quantify the comparable results and identify the correlations between design changes and building performance. I will also do a comparative analysis between IES VE and Green Building Studio. Green Building Studio is a free online service-based company. This analysis results will reveal the true value of the latest attempts to curb climate change via technology. Although this part of my D.Arch Project is not a requirement of the competition, I believe that any new data in the comparison between building simulation software’s is valuable to the AEC (Architecture, Engineering, and Construction) community

Empirical assessment of architecture-based reliability of open-source software

A number of analytical models have been proposed earlier for quantifying software reliability. Some of these models estimate the failure behavior of the software using black-box testing, which treats the software as a monolithic whole. With the evolution of component based software development, the necessity to use white-box testing increased. A few architecture-based reliability models, which use white-box approach, were proposed earlier and they have been validated using several small case studies and proved to be correct. However, there is a dearth of large-scale empirical data used for reliability analysis. This thesis enriches the empirical knowledge in software reliability engineering. We use a real, large-scale case study, GCC compiler, for our experiments. To the best of out knowledge, this is the most comprehensive case study ever used for software reliability analysis. The software is instrumented with a profiler, to extract the execution profiles of the test cases. The execution profiles form the basis for building the operational profile of the system, which describes the software usage. The test case failures are traced back to the faults in the source code to analyze the failure behavior of the components. These results are used to estimate the reliability of the software, as well as the uncertainty in the reliability analysis using entropy