Arcadia, a software development environment research project

The research objectives of the Arcadia project are two-fold: discovery and development of environment architecture principles and creation of novel software development tools, particularly powerful analysis tools, which will function within an environment built upon these architectural principles.Work in the architecture area is concerned with providing the framework to support integration while also supporting the often conflicting goal of extensibility. Thus, this area of research is directed toward achieving external integration by providing a consistent, uniform user interface, while still admitting customization and addition of new tools and interface functions. In an effort to also attain internal integration, research is aimed at developing mechanisms for structuring and managing the tools and data objects that populate a software development environment, while facilitating the insertion of new kinds of tools and new classes of objects.The unifying theme of work in the tools area is support for effective analysis at every stage of a software development project. Research is directed toward tools suitable for analyzing pre-implementation descriptions of software, software itself, and towards the production of testing and debugging tools. In many cases, these tools are specifically tailored for applicability to concurrent, distributed, or real-time software systems.The initial focus of Arcadia research is on creating a prototype environment, embodying the architectural principles, which supports Ada1 software development. This prototype environment is itself being developed in Ada.Arcadia is being developed by a consortium of researchers from the University of California at Irvine, the University of Colorado at Boulder, the University of Massachusetts at Amherst, TRW, Incremental Systems Corporation, and The Aerospace Corporation. This paper delineates the research objectives and describes the approaches being taken, the organization of the research endeavor, and current status of the work

Rational's experience using Ada for very large systems

The experience using the Rational Environment has confirmed the advantages forseen when the project was started. Interactive syntatic and semantic information makes a tremendous difference in the ease of constructing programs and making changes to them. The ability to follow semantic references makes it easier to understand exisiting programs and the impact of changes. The integrated debugger makes it much easier to find bugs and test fixes quickly. Taken together, these facilites have helped greatly in reducing the impact of ongoing maintenance of the ability to produce a new code. Similar improvements are anticipated as the same level of integration and interactivity are achieved for configuration management and version control. The environment has also proven useful in introducing personnel to the project and existing personnel to new parts of the system. Personnel benefit from the assistance with syntax and semantics; everyone benefits from the ability to traverse and understand the structure of unfamiliar software. It is often possible for someone completely unfamiliar with a body of code to use these facilities, to understand it well enough to successfully with a body of code to use these facilities to understand it well enough to successfully diagnose and fix bugs in a matter of minutes

Spacecraft attitude control using a smart control system

Traditionally, spacecraft attitude control has been implemented using control loops written in native code for a space hardened processor. The Naval Research Lab has taken this approach during the development of the Attitude Control Electronics (ACE) package. After the system was developed and delivered, NRL decided to explore alternate technologies to accomplish this same task more efficiently. The approach taken by NRL was to implement the ACE control loops using systems technologies. The purpose of this effort was to: (1) research capabilities required of an expert system in processing a classic closed-loop control algorithm; (2) research the development environment required to design and test an embedded expert systems environment; (3) research the complexity of design and development of expert systems versus a conventional approach; and (4) test the resulting systems against the flight acceptance test software for both response and accuracy. Two expert systems were selected to implement the control loops. Criteria used for the selection of the expert systems included that they had to run in both embedded systems and ground based environments. Using two different expert systems allowed a comparison of the real-time capabilities, inferencing capabilities, and the ground-based development environment. The two expert systems chosen for the evaluation were Spacecraft Command Language (SCL), and NEXTPERT Object. SCL is a smart control system produced for the NRL by Interface and Control Systems (ICS). SCL was developed to be used for real-time command, control, and monitoring of a new generation of spacecraft. NEXPERT Object is a commercially available product developed by Neuron Data. Results of the effort were evaluated using the ACE test bed. The ACE test bed had been developed and used to test the original flight hardware and software using simulators and flight-like interfaces. The test bed was used for testing the expert systems in a 'near-flight' environment. The technical approach, the system architecture, the development environments, knowledge base development, and results of this effort are detailed

Live Software Development with Dynamic Classes

Software modification at run-time can facilitate rapid prototyping, streamline development and debugging, and enable interactive educational programming environments. However, sup-porting live fine-grain program modification while reaping the benefits of a compiled type-safe language is a challenging problem. This paper presents fine-grain dynamic classes that support live object-oriented software development in which a program can be modified during execution. We present an implementation of dynamic classes in Java that does not require modification of the Java Virtual Machine. Our implementation supports full interoperability between instances of dynamic classes and compiled classes, including polymorphism, with minimal overhead. Changes to dynamic classes, such as the declaration of instance variables and methods, as well as the modification of statements and expressions within method bodies, take immediate effect on existing instances of those classes. We describe benefits of using dynamic classes in the context of a tightly integrated development environment

An evaluation of Ada for Al applications

Expert system technology seems to be the most promising type of Artificial Intelligence (AI) application for Ada. An expert system implemented with an expert system shell provides a highly structured approach that fits well with the structured approach found in Ada systems. The current commercial expert system shells use Lisp. In this highly structured situation a shell could be built that used Ada just as well. On the other hand, if it is necessary to deal with some AI problems that are not suited to expert systems, the use of Ada becomes more problematical. Ada was not designed as an AI development language, and is not suited to that. It is possible that an application developed in say, Common Lisp could be translated to Ada for actual use in a particular application, but this could be difficult. Some standard Ada packages could be developed to make such a translation easier. If the most general AI programs need to be dealt with, a Common Lisp system integrated with the Ada Environment is probably necessary. Aside from problems with language features, Ada, by itself, is not well suited to the prototyping and incremental development that is well supported by Lisp

Run-Time Verification of Black-Box Components Using Behavioral Specifications: An Experience Report on Tool Development

We introduce a generic component-based design of a run-time checker, identify its components and their requirements, and evaluate existing state of the art tools instantiating each component