Semantics-Based Change-Merging of Abstract Data Types

Maintaining any software is difficult. Whenever an evolutionary change is made to the base version of a program and the new version of the program is created, changes made to the base version of the software must be made to the new version. The answer is to build the software initially with the knowledge that it will change and that the base version will evolve. In other words, change-merging of software is a possible solution. All the work in this area has been done on program integration, change-merging of PSDL programs and software prototypes. The present work explores the possibility of combining the results of two independent updates of an abstract data type into a merged version that is both correct and safe. This report describes a developing theory for semantics-based change-merging of abstract data types

Semantic networks

AbstractA semantic network is a graph of the structure of meaning. This article introduces semantic network systems and their importance in Artificial Intelligence, followed by I. the early background; II. a summary of the basic ideas and issues including link types, frame systems, case relations, link valence, abstraction, inheritance hierarchies and logic extensions; and III. a survey of ‘world-structuring’ systems including ontologies, causal link models, continuous models, relevance, formal dictionaries, semantic primitives and intersecting inference hierarchies. Speed and practical implementation are briefly discussed. The conclusion argues for a synthesis of relational graph theory, graph-grammar theory and order theory based on semantic primitives and multiple intersecting inference hierarchies

Towards the integration of functions, relations and types in an AI programming language

This paper describes the design and implementation of the programming language PC-Life. This language integrates the functional and the Logic-oriented programming style and feature types supporting inheritance. This combination yields a language particularly suited to knowledge representation, especially for application in computational linguistics

Knowledge-based support in Non-Destructive Testing for health monitoring of aircraft structures

Maintenance manuals include general methods and procedures for industrial maintenance and they contain information about principles of maintenance methods. Particularly, Non-Destructive Testing (NDT) methods are important for the detection of aeronautical defects and they can be used for various kinds of material and in different environments. Conventional non-destructive evaluation inspections are done at periodic maintenance checks. Usually, the list of tools used in a maintenance program is simply located in the introduction of manuals, without any precision as regards to their characteristics, except for a short description of the manufacturer and tasks in which they are employed. Improving the identification concepts of the maintenance tools is needed to manage the set of equipments and establish a system of equivalence: it is necessary to have a consistent maintenance conceptualization, flexible enough to fit all current equipment, but also all those likely to be added/used in the future. Our contribution is related to the formal specification of the system of functional equivalences that can facilitate the maintenance activities with means to determine whether a tool can be substituted for another by observing their key parameters in the identified characteristics. Reasoning mechanisms of conceptual graphs constitute the baseline elements to measure the fit or unfit between an equipment model and a maintenance activity model. Graph operations are used for processing answers to a query and this graph-based approach to the search method is in-line with the logical view of information retrieval. The methodology described supports knowledge formalization and capitalization of experienced NDT practitioners. As a result, it enables the selection of a NDT technique and outlines its capabilities with acceptable alternatives

Simplifying the Analysis of C++ Programs

Based on our experience of working with different C++ front ends, this thesis identifies numerous problems that complicate the analysis of C++ programs along the entire spectrum of analysis applications. We utilize library, language, and tool extensions to address these problems and offer solutions to many of them. In particular, we present efficient, expressive and non-intrusive means of dealing with abstract syntax trees of a program, which together render the visitor design pattern obsolete. We further extend C++ with open multi-methods to deal with the broader expression problem. Finally, we offer two techniques, one based on refining the type system of a language and the other on abstract interpretation, both of which allow developers to statically ensure or verify various run-time properties of their programs without having to deal with the full language semantics or even the abstract syntax tree of a program. Together, the solutions presented in this thesis make ensuring properties of interest about C++ programs available to average language users

Mining Multiple Related Tables Using Object-Oriented Model

An object-oriented database is represented by a set of classes connected by their class inheritance hierarchy through superclass and subclass relationships. An object-oriented database is suitable for capturing more details and complexity for real world data. Existing algorithms for mining multiple databases are either Apriori-based or machine learning techniques, but are not suitable for mining multiple object-oriented databases. This thesis proposes an object-oriented class model and database schema, and a series of class methods including that for object-oriented join ( OOJoin) which joins superclass and subclass tables by matching their type and super type relationships, mining Hierarchical Frequent Patterns ( MineHFPs) from multiple integrated databases by applying an extended TidFP technique which specifies the class hierarchy by traversing the multiple database inheritance hierarchy. This thesis also extends map-gen join method used in TidFP algorithm to oomap-gen join for generating k-itemset candidate pattern to reduce the candidate itemset generation by indexing the (k-1)-itemset candidate pattern using two position codes of start position and end position codes tied to inheritance hierarchy level. Experiments show that the proposed MineHFPs algorithm for mining hierarchical frequent patterns is more effective and efficient for complex queries