The robotics experience

End user involvement and input into the design and evaluation of information systems has been recognized as being a critical success factor in the adoption of information systems. Nowhere is this need more critical than in the design of health information systems. Consistent with evidence from the general software engineering literature, the degree of user input into design of complex systems has been identified as one of the most important factors in the success or failure of complex information systems. The participatory approach goes beyond user-centered design and co-operative design approaches to include end users as more active participants in design ideas and decision making. Proponents of participatory approaches argue for greater end user participation in both design and evaluative processes. Evidence regarding the effectiveness of increased user involvement in design is explored in this contribution in the context of health IT. The contribution will discuss several approaches to including users in design and evaluation. Challenges in IT evaluation during participatory design will be described and explored along with several case studies.

In various fields of computer science, rapidly growing hardware power, such as high-speed network, high-performance CPU, huge disk capacity, and large memory space, has been fruitfully harnessed. Examples of such usage are large scale data and web mining, grid computing, and multimedia environments. We propose that such rich hardware can also catapult software engineering to the next level. Huge amounts of software engineering data can be systematically collected and organized from tens of thousands of projects inside organizations, or from outside an organization through the Internet. The collected data can be analyzed extensively to extract and correlate multi-project knowledge for improving organization-wide productivity and quality. We call such an approach for software engineering Mega Software Engineering. In this paper, we propose the concept of Mega Software Engineering, and demonstrate some novel data analysis characteristic of Mega Software Engineering. We describe a framework for enabling Mega Software Engineering.KeywordsSoftware EngineeringSoftware EngineerSoftware ProjectCollaborative FilterGlobal Software DevelopmentThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Authors

PurposeThis paper deals with the collaborative design of electromagnetic devices over the internet network. The design is made by both mechanical and electrical engineers. So, the paper tries to show the importance but also constraints to size such a system using a collaborative optimisation process.Design/methodology/approachThe paper compares two approaches in order to size an electromechanical actuator between mechanical and electrical engineers. In the first one, each profession designs its part, and only common constrained are negotiated. This can result in a design process with many iterations. In the second one, electrical and mechanical engineers built together a common model of the structure and a common list of specifications: this allows a global optimisation that is more efficient.FindingsThe main result of the paper is that the second approach in which a global model is built between electrical and mechanical engineers is more efficient.Originality/valueThe originality of the paper is to explore the problems and difficulties of an optimisation of an electromechanical device between engineers of different culture working together over the internet network.

The crowdsourcing literature has shown that domain experts are not always the best solvers for complex system design problems. Novices and specialists in adjacent domains can, under certain conditions, provide novel solutions at lower costs. Additionally, the best types of solvers for different sub-problems are dependent on the architecture of complex systems. The assignment of solvers based on the architecture, referred to as Solver-Aware System Architecting (SASA), expands traditional system architecting practices by considering solver characteristics and contractual incentive mechanisms in the design process and aims to improve complex system design and innovation by leveraging the strengths of domain experts, crowds, and specialists for different parts of the problem. Given the complexity of system design problems and the variety of solvers available, it is desirable to have heuristics to guide solver assignment to different problems. Developing effective heuristics for solver assignments in complex system design is challenging due to a large number of possible combinations of problem-solver pairs. To address this challenge, this paper presents a computational approach using a multi-armed bandit (MAB) formulation to generate heuristics for solver assignment. The approach is demonstrated using a simple and idealized problem of golf, which has characteristics similar to design problems, including how the problem is decomposed into sub-problems, and solved by different solvers. The results show that the proposed approach is effective in deriving a rich set of heuristics for the golf problem, and can be extended in the future to more complex systems design problems.

This paper describes an approach to integrating software engineering concepts and principles into the Electrical and Computer Engineering (ECE) and Computer Science (CS) curricula. Our philosophy is to apply software engineering techniques throughout the ECE/CS curricula to leverage learning in non-software engineering courses. Our technique is to seek out faculty interested in innovative teaching techniques, consult with them to identify some way that they and we feel a course they are teaching could benefit pedagogically from some application of software engineering, and work with them to make that happen. The chief intended result is to leverage learning in diverse courses, thereby benefiting pedagogy of non-software engineering topics. An auxiliary important result is to increase awareness among both students and faculty of the software engineering body of knowledge. Many software engineering approaches to understanding and solving problems in the software life cycle can also address a variety of learning needs across disciplines in ECE and CS. For example, there are software engineering techniques that can emphasize visualization (benefiting students who respond to the visual modality), logical sequences (benefiting sequential learners), summarizations (benefiting global learners), and others. Additionally, general issues of teamwork and the engineering life cycle can be addressed. We have applied our approach to a diverse set of electrical engineering and computing courses at four universities in the US and Canada, and based on those experiences we believe we have identified a win-win paradigm that can be a model for integration of software engineering concepts into electrical engineering and computing curricula.

This article provides a concrete example for using and creating a virtual environment for computer-aided design of complex systems. The subject area is design, and the object of research is an aircraft. CAD creates a parameterized 3D model, which is demonstrated and processed on a virtual stage using special equipment. Special equipment such as the HTC Vive Pro virtual reality helmet and the included controllers. The virtual assistant of the designer allows you to create detailed parameterized models of an aircraft, in particular, a transport aircraft based on the An-124 Ruslan, and virtual reality helps the user to learn more about the created project and make the necessary optimization edits directly in VR space. By changing the model in VR space, it will change in the main project. The work is a continuation of the development of a decision-making system, a virtual assistant to the designer: "Robot designer", whose application interface has been defined. The main control menu for the user in virtual space is shown, and the aircraft with the fuselage skin and cockpit removed is also shown. Plans for further use of virtual reality technology in the design of complex systems and training of specialists with the profile of aircraft engineers are presented.

Design of complex systems in the presence of large uncertainties: A statistical approach

Guest Editorial

“Software engineering entails the understanding and application of engineering principles, design skills, good management practice, computer science and mathematical formalism. It is the task of the software engineer to draw together these separate areas of expertise and bring them to bear upon the specification, design, verification, implementation, testing, documentation and maintenance of complex and large scale software systems.”

The Defense Advanced Research Projects Agency (DARPA) created the Fast, Adaptable, Next-Generation Ground Vehicle (FANG) program to design and develop a new heavy, amphibious infantry fighting vehicle (IFV). DARPA, through the FANG program, is undertaking a radically novel approach to the design and manufacture of complex defense systems, and is hosting a series of prize-based design competitions. These are called the FANG Challenges, and their products will be progressively more complex vehicle subsystems, culminating in the design of a full IFV. They leverage the META design tools and the VehicleFORGE collaboration environment to significantly change the design experience and widen the aperture for design innovation. The META tool suite is a set of free, open source tools for compositional design synthesis at multiple levels of abstraction, design trade space exploration, metrics assessment, and probabilistic verification of system correctness. VehicleFORGE is an open source development collaboration environment for the creation of large, complex systems by numerous unaffiliated designers with the goal of democratizing the design innovation process by engaging several orders of magnitude more talent than the current industry model. This work summarizes the results from the first FANG challenge through analysis of participants, team structures, and the designs created.

As in any academic discipline, the evaluation of proposed methodologies and techniques is of vital importance for assessing the validity of novel ideas or findings in Software Engineering. Over the years, a large number of evaluation approaches have been employed, some of them drawn from other domains and other particularly developed for the needs of software engineering related research. In this paper we present the results of a survey of evaluation techniques that have been utilized in research papers that appeared in three leading software engineering journal and propose a taxonomy of evaluation approaches which might be helpful towards the organization of knowledge regarding the different strategies for the validation of research outcomes. The applicability of the proposed taxonomy has been evaluated by classifying the articles retrieved from ICSE'2012.

Machines are omnipresent. They produce, they transport. Machines facilitate work and assist. The increasing penetration of mechanical engineering by information technology enables considerable benefits. This circumstance is expressed by the term mechatronics, which means the close interaction of mechanics, electronics, control engineering and software engineering to improve the behavior of a technical system. The progressive integration of information technology will enable mechatronic systems with partial intelligence. We refer to such systems as self-optimizing systems. Self-optimizing systems have the ability to react autonomously and flexibly on changing operation conditions. The design of such systems is an even more interdisciplinary task than the design of conventional mechatronic systems. Additionally to mechanical, electrical, control and software engineers also experts from mathematical optimization and artificial intelligence are involved. As a consequence a domain-spanning methodology is necessary in order to guarantee an effective work flow between the participating developers from various domains and their domain-specific methods, terminologies and solutions. This contribution presents such a methodology. The main focus, however, lies on harnessing of experimental knowledge for the development of self-optimizing systems. This includes the generation and storage of once proven design solutions as well as a tool for the effective and domain-spanning reuse.

Engineers are faced with two major challenges when carrying out the thermal-fluid design of a complex system consisting of many interacting components such as the PBMR power plant. The first challenge is to predict the performance of all the individual thermal-fluid components. The second challenge is to predict the performance of the integrated plant consisting of all its sub-systems. The complexity associated with the thermal-fluid design of complex systems requires the use of a variety of analysis techniques and simulation tools. These range from simple one-dimensional models that do not capture all the significant physical phenomena, to large-scale three-dimensional CFD codes that, for practical reasons, can not simulate the entire plant as a single integrated model. In the systems CFD approach a network code serves as the framework to link the models of the various components together and to control the solution. The models of the components can be of varying degrees of complexity. These can range from simple lumped models to complex fully three-dimensional CFD models. This paper gives a brief overview of the systems CFD (SCFD) approach and an overview of the SCFD model of the pebble bed nuclear reactor that was developed.

Currently, the design of complex systems is carried out by developing one of the possible options, which largely depends on the individual abilities and experience of developers. The implementation of this option in the future will be determined by the persistence and organizational abilities of the project authors, often regardless of the quality of the chosen option. The theory of building complex information systems, which include automated control systems, and the features of choosing the structure of such systems have not been sufficiently developed to date. At the same time, there is an opinion that if the author has not considered at least three alternative variants of structural schemes then the possibility of choosing the most preferred solution is very small, and the less the more complex the system is. A brief analysis of the advantages and disadvantages of various methods of constructing a generalized quality indicator has shown that the resulting objective quality function, constructed taking into account the physical connections of the automated control system with other systems, united by common functioning and joint placement as part of a technical complex, is characterized by the smallest elements of subjectivity and conditionality.