Learning from AI : new trends in database technology

Recently some researchers in the areas of database data modelling and knowledge representations in artificial intelligence have recognized that they share many common goals. In this survey paper we show the relationship between database and artificial intelligence research. We show that there has been a tendency for data models to incorporate more modelling techniques developed for knowledge representations in artificial intelligence as the desire to incorporate more application oriented semantics, user friendliness, and flexibility has increased. Increasing the semantics of the representation is the key to capturing the "reality" of the database environment, increasing user friendliness, and facilitating the support of multiple, possibly conflicting, user views of the information contained in a database

Debugging Scandal: The Next Generation

In 1997, the general lack of debugging tools was termed "the debugging scandal". Today, as new languages are emerging to support software evolution, once more debugging support is lagging. The powerful abstractions offered by new languages are compiled away and transformed into complex synthetic structures. Current debugging tools only allow inspection in terms of this complex synthetic structure; they do not support observation of program executions in terms of the original development abstractions. In this position paper, we outline this problem and present two emerging lines of research that ease the burden for debugger implementers and enable developers to debug in terms of development abstractions. For both approaches we identify language-independent debugger components and those that must be implemented for every new language. One approach restores the abstractions by a tool external to the program. The other maintains the abstractions by using a dedicated execution environment, supporting the relevant abstractions. Both approaches have the potential of improving debugging support for new languages. We discuss the advantages and disadvantages of both approaches, outline a combination thereof and also discuss open challenges

Using automated source code analysis for software evolution

Software maintenance is one of the most expensive and time-consuming phases in the software life-cycle. The size and complexity of commercial applications probably present the greatest difficulty that maintainers face when making changes to their applications. As a result of the corresponding loss of understanding, business knowledge encapsulated within the system becomes fragmented, and any changes made as a result of new business initiatives become difficult to implement and hence may mean a loss of business opportunities. This paper outlines an approach to regaining understanding of software which has been used in the Release project at Durham University. This approach involves determining the calling structure of a program in terms of a call-graph, and from this call-graph extracting a dominance tree. Various problems which have been encountered during the construction of tools to perform this task are described

Understanding object-oriented source code from the behavioural perspective

Comprehension is a key activity that underpins a variety of software maintenance and engineering tasks. The task of understanding object-oriented systems is hampered by the fact that the code segments that are related to a user-level function tend to be distributed across the system. We introduce a tool-supported code extraction technique that addresses this issue. Given a minimal amount of information about a behavioural element of the system that is of interest (such as a use-case), it extracts a trail of the methods (and method invocations) through the system that are needed in order to achieve an understanding of the implementation of the element of interest. We demonstrate the feasibility of our approach by implementing it as part of a code extraction tool, presenting a case study and evaluating the approach and tool against a set of established criteria for program comprehension tools

Study and development of techniques for automatic control of remote manipulators

An overall conceptual design for an autonomous control system of remote manipulators which utilizes feedback was constructed. The system consists of a description of the high-level capabilities of a model from which design algorithms are constructed. The autonomous capability is achieved through automatic planning and locally controlled execution of the plans. The operator gives his commands in high level task-oriented terms. The system transforms these commands into a plan. It uses built-in procedural knowledge of the problem domain and an internal model of the current state of the world