46303239
Object Orientation in Hierarchical Predicate Transition Nets
In this paper, an approach of using hierarchical predicate transition nets (HPrTNs in the sequel) for object-oriented specification is proposed. The realization of various object-oriented features (including encapsulation, inheritance, and polymorphism) in HPrTNs is presented and is demonstrated with examples. We believe that the approach can achieve the benefits of the object-oriented methods while maintaining the analyzability of HPrTNs.
31879969
A Method for Constructing Algebraic Petri Nets
Algebraic Petri nets are a powerful formal method for specifying concurrent and distributed systems. We present a new method of constructing algebraic Petri net specifications by establishing a relationship between algebraic Petri nets with structured analysis methods. Algebraic Petri net specifications are systematically derived from data flow diagrams, a data dictionary, and decision table process specifications. Our results facilitate the application of algebraic Petri nets and also provide a potential analysis technique for informal specifications written in structured analysis methods.
17445618
A Formal Definition of Hierarchical Predicate Transition Nets
Hierarchical predicate transition nets have recently been introduced as a visual formalism for specifying complex reactive systems. They extend predicate transition nets with hierarchical structures so that large systems can be specified and understood stepwisely, and thus are more suitable for real-world applications. In this paper, we provide a formal syntax and an algebraic semantics for hierarchical predicate transition nets, which establish the theory of hierarchical predicate transition nets for precise specification and formal reasoning.
20452185
A methodology for test selection
Software creation requires not only testing during the development cycle by the development staff, but also independent testing following the completion of the implementation. However in the latter case, the amount of testing that can be carried out is often limited by time and resources. At the very most, independent testing can be expected to provide 100% test coverage of the test requirements (or specifications) associated with the software element with the minimum of effort. This paper describes a methodology employing integer programming by which the amount of testing required to provide the maximum possible test coverage of the test requirements (for the given test set) is assured while at the same time minimizing the total number of tests to be included in a test suite. A collateral procedure provides recommendations on which tests might be eliminated if less than 100% test coverage of the test requirements is permitted. This latter procedure will be useful in determining the risk of not running the minimum set of tests for 100% test coverage. A third process selects from the test matrix the set of tests to be applied to the system following maintenance modification of any test requirements-- that is, to provide a submatrix for regression testing. The potential benefits for applying the integer programming technique in test data selection is also discussed.
8640545
Refining edge detection within spiral architecture
Detection of edge points of 3-dimensional physical object in a 2-dimensional image is one of the main research areas of computer vision. Object contour detection and object recognition rely heavily on edge detection. The Spiral Architecture, a relatively new image structure, possesses powerful computational features that are pertinent to the vision process. In this paper, we present an edge detection scheme using Gaussian Multi-resolution Theory. The detection algorithm reduces noise and unnecessary details of the image. This algorithm is applied to obtain the edge maps of some well-known images for image processing.
14477095
Learning and Incorporating Top-Down Cues in Image Segmentation
Bottom-up approaches, which rely mainly on continuity principles, are often insufficient to form accurate segments in natural images. In order to improve performance, recent methods have begun to incorporate top-down cues, or object information, into segmentation. In this paper, we propose an approach to utilizing category-based information in segmentation, through a formulation as an image labelling problem. Our approach exploits bottom-up image cues to create an over-segmented representation of an image. The segments are then merged by assigning labels that correspond to the object category. The model is trained on a database of images, and is designed to be modular: it learns a number of image contexts, which simplify training and extend the range of object classes and image database size that the system can handle. The learning method estimates model parameters by maximizing a lower bound of the data likelihood. We examine performance on three real-world image databases, and compare our system to a standard classifier and other conditional random field approaches, as well as a bottom-up segmentation method.
949912
Replicated Shared Object Model for Edge Detection with Spiral Architecture
Edge detection in computer vision and image processing is a process which detects one kind of significant features appearing as discontinuities in intensities. A parallel edge detection algorithm based on Spiral Architeture is designed in this paper by a Replicated Shared Object Model (RSOM). We use this approach to meet the need of replicated object management, update propagation, underlying communication and consistency maintenance among replicated objects.
467326
An efficient parallel algorithm for finding rectangular duals of plane triangular graphs
We present an efficient parallel algorithm for constructing rectangular duals of plane triangular graphs. This problem finds applications in VLSI design and floor-planning problems. No NC algorithm for solving this problem was previously known. The algorithm takesO(log2n) time withO(n) processors on a CRCW PRAM, wheren is the number of vertices of the graph.
25659954
An Improved Algorithm for the Planar 3-Cut Problem
Abstract A 3-cut of a connected graph G is a subset of edges which, when deleted, separates G into three connected components. In this paper we present an O ( n log n ) algorithm for finding a minimum 3-cut in planar graphs. Our algorithm improves the best previously known algorithm for the problem by an O( n log n) factor.