Prototyping a process-centered environment

This paper describes an experimental system developed and used as a vehicle for prototyping the Arcadia-1 software development environment. Prototyping is viewed as a knowledge acquisition process and is used to reduce risks in software development by gaining rapid feedback about the suitability of a production system before the system is completed. Prototyping a software development environment is particularly important due to the lack of experience with them. There is an acute need to acquire knowledge about user interaction requirements for software environments. These needs are especially important for the Arcadia project, as it is one of the first attempts to construct a process-centered environment. Our prototyping effort addresses questions about effective interaction with a process-centered environment by simulating how Arcadia-1 would interact with users in a representative range of usage scenarios. We built a prototyping system, called PRODUCER, and used it to generate a variety of prototypes simulating user interactions with Arcadia-1 process programs.Experience with PRODUCER indicates that our approach is effective at risk reduction. The prototypes greatly improved communication with our customer. They confirmed some of our design decisions but also redirected our research efforts as a result of unexpected insight. We also found that prototyping usage scenarios provides conceptual guides and design information for process programmers. Most of the benefits of our prototyping effort derive from developing and interacting with usage scenarios, so our approach is generalizable to other prototyping systems. This paper reports on our prototyping approach and our experience in prototyping a process-centered environment

Survey of Technologies for Web Application Development

Web-based application developers face a dizzying array of platforms, languages, frameworks and technical artifacts to choose from. We survey, classify, and compare technologies supporting Web application development. The classification is based on (1) foundational technologies; (2)integration with other information sources; and (3) dynamic content generation. We further survey and classify software engineering techniques and tools that have been adopted from traditional programming into Web programming. We conclude that, although the infrastructure problems of the Web have largely been solved, the cacophony of technologies for Web-based applications reflects the lack of a solid model tailored for this domain.Comment: 43 page

ImageJ2: ImageJ for the next generation of scientific image data

ImageJ is an image analysis program extensively used in the biological sciences and beyond. Due to its ease of use, recordable macro language, and extensible plug-in architecture, ImageJ enjoys contributions from non-programmers, amateur programmers, and professional developers alike. Enabling such a diversity of contributors has resulted in a large community that spans the biological and physical sciences. However, a rapidly growing user base, diverging plugin suites, and technical limitations have revealed a clear need for a concerted software engineering effort to support emerging imaging paradigms, to ensure the software's ability to handle the requirements of modern science. Due to these new and emerging challenges in scientific imaging, ImageJ is at a critical development crossroads. We present ImageJ2, a total redesign of ImageJ offering a host of new functionality. It separates concerns, fully decoupling the data model from the user interface. It emphasizes integration with external applications to maximize interoperability. Its robust new plugin framework allows everything from image formats, to scripting languages, to visualization to be extended by the community. The redesigned data model supports arbitrarily large, N-dimensional datasets, which are increasingly common in modern image acquisition. Despite the scope of these changes, backwards compatibility is maintained such that this new functionality can be seamlessly integrated with the classic ImageJ interface, allowing users and developers to migrate to these new methods at their own pace. ImageJ2 provides a framework engineered for flexibility, intended to support these requirements as well as accommodate future needs

Simulation of networks of spiking neurons: A review of tools and strategies

We review different aspects of the simulation of spiking neural networks. We start by reviewing the different types of simulation strategies and algorithms that are currently implemented. We next review the precision of those simulation strategies, in particular in cases where plasticity depends on the exact timing of the spikes. We overview different simulators and simulation environments presently available (restricted to those freely available, open source and documented). For each simulation tool, its advantages and pitfalls are reviewed, with an aim to allow the reader to identify which simulator is appropriate for a given task. Finally, we provide a series of benchmark simulations of different types of networks of spiking neurons, including Hodgkin-Huxley type, integrate-and-fire models, interacting with current-based or conductance-based synapses, using clock-driven or event-driven integration strategies. The same set of models are implemented on the different simulators, and the codes are made available. The ultimate goal of this review is to provide a resource to facilitate identifying the appropriate integration strategy and simulation tool to use for a given modeling problem related to spiking neural networks.Comment: 49 pages, 24 figures, 1 table; review article, Journal of Computational Neuroscience, in press (2007

A Runtime Software Visualization Environment

As software systems become more complex, so does the task of understanding them. To modify even a simple component of a complex system, at least a rudimentary understanding of the structure and behavior of the whole system is necessary. Although currently available development tools can provide a static representation of a complex system, these utilities are severely limited and prohibitively expensive. As a result, most programmers working on large software systems today resort to classic debuggers and time-consuming plain-text searches through hundreds or thousands of source files. This proposal describes a software development environment that uses static representations of hierarchically structured source code side by side with dynamic visualizations of software systems as they run. This environment provides an intuitive, visual means of easily comprehending complex systems, and has been provided as an open-source development tool for both professionals and students of software engineering

A Software Framework for Aircraft Simulation

The National Aeronautics and Space Administration Dryden Flight Research Center has a long history in developing simulations of experimental fixed-wing aircraft from gliders to suborbital vehicles on platforms ranging from desktop simulators to pilot-in-the-loop/aircraft-in-the-loop simulators. Regardless of the aircraft or simulator hardware, much of the software framework is common to all NASA Dryden simulators. Some of this software has withstood the test of time, but in recent years the push toward high-fidelity user-friendly simulations has resulted in some significant changes. This report presents an overview of the current NASA Dryden simulation software framework and capabilities with an emphasis on the new features that have permitted NASA to develop more capable simulations while maintaining the same staffing levels