35807335
Comments on Program Slicing
This correspondence points out some of the problems with Weiser's algorithm [5] for computing program slices. Corrections are made to Weiser's algorithm. It is shown how Weiser's algorithm can be amended to handle loops. Advantages of the Bergeretti and Carre's approach [1] are discussed.
30262171
Improving defect removal effectiveness for software development
The paper first reviews the industry statistics on defects, presents a model of defect removal, then develops the relationships between the defect removal effectiveness of different defect removal phases. The defect removal effectiveness of an average organization is determined based on published data. Combining the industry data with the defect removal model, insights into improvement of the defect removal process can be gained. It is determined that the defect removal effectiveness of individual phases cannot be higher than that of the overall development process. Also, introducing inspection to the software development process will certainly allow an average organization to achieve higher defect removal effectiveness.
18767073
Fitting Ellipses to a Region with Application in Calligraphic Stroke Reconstruction
Given a region, it is a challenge to find a set of primitive shapes such as rectangles, circles or ellipses to cover it. This is in fact a set-covering problem, which is known to be NP-hard. The focus of this paper is on fitting a set of ellipses onto an image region. This problem was first formulated by identifying a number of criteria required for the ellipse fitting. A solution is then proposed for automatically determining the set of ellipses that best fits onto an image region. The proposed ellipse fitting algorithm has also been applied to strokes forming characters of Chinese calligraphic artwork. The results show that our proposed algorithm generates ellipses fitting onto stroke regions and capturing the characteristics of the strokes during turning, tilting and back-trace.
17124839
Separating Exponentially Ambiguous Finite Automata from Polynomially Ambiguous Finite Automata
We resolve an open problem raised by Ravikumar and Ibarra [SIAM J. Comput., 18 (1989), pp. 1263--1282] on the succinctness of representations relating to the types of ambiguity of finite automata. We show that there exists a family of nondeterministic finite automata {An} over a two-letter alphabet such that, for any positive integer n, An is exponentially ambiguous and has n states, whereas the smallest equivalent deterministic finite automaton has 2n states, and any smallest equivalent polynomially ambiguous finite automaton has 2n -1 states.
1007735
Structurally Unambiguous Finite Automata
We define a structurally unambiguous finite automaton (SUFA) to be a nondeterministic finite automaton (NFA) with one starting state q0 such that for all input strings w and for any state q, there is at most one path from q0 to q that consumes w. The definition of SUFA differs from the usual definition of an unambiguous finite automaton (UFA) in that the new definition is defined in terms of the transition logic of the finite automaton, and is independent of the choice of final states. We show that SUFA can be exponentially more succinct in the number of states than UFA and MDFA (deterministic finite automata with multiple initial states). Some interesting examples of SUFA are given. We argue that SUFA is a meaningful concept, and can have practical importance as it can implemented efficiently on synchronous models of parallel computation.
38923052
Reconstruction of piecewise chaotic dynamics using a multiple model approach
In this paper we propose using a multiple model (MM) predictor to reconstruct piecewise chaotic dynamic. The motivation relies on the observation that conventional single model is usually incapable of reconstructing the piecewise dynamic properly because a piecewise map is non-differentiable. In our approach, multiple radial basis function (RBF) neural nets are used to model the dynamic in different partition intervals. Switching between different intervals could be estimated by a nonlinear gate model. In particular, an Expectation-Maximization (EM) algorithm is employed to train the MM-RBF. Compared to the conventional approach, the proposed MM is shown to greatly improve the reconstruction performance for piecewise chaotic dynamic. We further apply it to combat channel distortions in an analog chaotic spread spectrum (SS) system. It is found that the proposed method has satisfactory equalization performance even when channel effect is strong.
37235208
Model-Based Analysis of Chinese Calligraphy Images