ARROWSMITH-P: A prototype expert system for software engineering management

Although the field of software engineering is relatively new, it can benefit from the use of expert systems. Two prototype expert systems were developed to aid in software engineering management. Given the values for certain metrics, these systems will provide interpretations which explain any abnormal patterns of these values during the development of a software project. The two systems, which solve the same problem, were built using different methods, rule-based deduction and frame-based abduction. A comparison was done to see which method was better suited to the needs of this field. It was found that both systems performed moderately well, but the rule-based deduction system using simple rules provided more complete solutions than did the frame-based abduction system

Advanced technologies for Mission Control Centers

Advance technologies for Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: technology needs; current technology efforts at GSFC (human-machine interface development, object oriented software development, expert systems, knowledge-based software engineering environments, and high performance VLSI telemetry systems); and test beds

Expert system verification concerns in an operations environment

The Space Shuttle community is currently developing a number of knowledge-based tools, primarily expert systems, to support Space Shuttle operations. It is proposed that anticipating and responding to the requirements of the operations environment will contribute to a rapid and smooth transition of expert systems from development to operations, and that the requirements for verification are critical to this transition. The paper identifies the requirements of expert systems to be used for flight planning and support and compares them to those of existing procedural software used for flight planning and support. It then explores software engineering concepts and methodology that can be used to satisfy these requirements, to aid the transition from development to operations and to support the operations environment during the lifetime of expert systems. Many of these are similar to those used for procedural hardware

Reliability Analysis of Concurrent Systems using LTSA

The analysis for software dependability is considered an important task within the software engineering life cycle. However, it is often impossible to carry out this task due to the complexity of available tools, lack of expert personnel and time-to-market pressures. As a result, released software versions may present unverified dependability properties subjecting customers to blind software reliability assessment. In particular, concurrent systems present certain behaviour that require a more complex system analysis not easily grasped at system design and architecture level

The integration of automated knowledge acquisition with computer-aided software engineering for space shuttle expert systems

A prediction was made that the terms expert systems and knowledge acquisition would begin to disappear over the next several years. This is not because they are falling into disuse; it is rather that practitioners are realizing that they are valuable adjuncts to software engineering, in terms of problem domains addressed, user acceptance, and in development methodologies. A specific problem was discussed, that of constructing an automated test analysis system for the Space Shuttle Main Engine. In this domain, knowledge acquisition was part of requirements systems analysis, and was performed with the aid of a powerful inductive ESBT in conjunction with a computer aided software engineering (CASE) tool. The original prediction is not a very risky one -- it has already been accomplished

Proceedings of Tenth Annual Software Engineering Workshop

Papers are presented on the following topics: measurement of software technology, recent studies of the Software Engineering Lab, software management tools, expert systems, error seeding as a program validation technique, software quality assurance, software engineering environments (including knowledge-based environments), the Distributed Computing Design System, and various Ada experiments

A First Course in Software Engineering for Aerospace Engineers

Software is a critical component of mission capability in all aerospace systems. This capability is realized directly through the use of onboard software, and enabled through the use of software on ground support systems. Students attending an aerospace engineering program come with a highly diversified background in software development ranging from novice user to expert programmer. A first course in software development has to account for the diversity, and as an outcome provide both a common vocabulary, as well as a common baseline of skills. This paper presents our learning from designing and teaching such a course for aerospace engineering undergraduates

Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed

Software life cycle methodologies and environments

Products of this project will significantly improve the quality and productivity of Space Station Freedom Program software processes by: improving software reliability and safety; and broadening the range of problems that can be solved with computational solutions. Projects brings in Computer Aided Software Engineering (CASE) technology for: Environments such as Engineering Script Language/Parts Composition System (ESL/PCS) application generator, Intelligent User Interface for cost avoidance in setting up operational computer runs, Framework programmable platform for defining process and software development work flow control, Process for bringing CASE technology into an organization's culture, and CLIPS/CLIPS Ada language for developing expert systems; and methodologies such as Method for developing fault tolerant, distributed systems and a method for developing systems for common sense reasoning and for solving expert systems problems when only approximate truths are known

Machine learning research 1989-90

Multifunctional knowledge bases offer a significant advance in artificial intelligence because they can support numerous expert tasks within a domain. As a result they amortize the costs of building a knowledge base over multiple expert systems and they reduce the brittleness of each system. Due to the inevitable size and complexity of multifunctional knowledge bases, their construction and maintenance require knowledge engineering and acquisition tools that can automatically identify interactions between new and existing knowledge. Furthermore, their use requires software for accessing those portions of the knowledge base that coherently answer questions. Considerable progress was made in developing software for building and accessing multifunctional knowledge bases. A language was developed for representing knowledge, along with software tools for editing and displaying knowledge, a machine learning program for integrating new information into existing knowledge, and a question answering system for accessing the knowledge base