Programming and Computer Software最新文献

Abstract

Different implementations of Clifford algebra: spinors, quaternions, and geometric algebra, are used to describe physical and technical systems. The geometric algebra formalism is a relatively new approach, destined to be used primarily by engineers and applied researchers. In a number of works, the authors examined the implementation of the geometric algebra formalism for computer algebra systems. In this article, the authors extend elliptic geometric algebra to hyperbolic space-time algebra. The results are illustrated by different representations of Maxwell’s equations. Using a computer algebra system, Maxwell’s vacuum equations in the space-time algebra representation are converted to Maxwell’s equations in vector formalism. In addition to practical application, the authors would like to draw attention to the didactic significance of these studies.

Abstract

A method to calculate partial sums of some multiple numerical series arising when searching for the resultant of a polynomial and an entire function is proposed. One can apply a symbolic algorithm that uses recurrent Newton formulas to find power sums of roots included in this formula without finding the very roots of the system. The algorithm that implements the proposed approach to calculate partial sums of multiple numerical series is implemented in Maple. Examples of using this algorithm to find partial sums of some classes of multiple numerical series are given.

Abstract

In this paper, we continue to consider the problem of recovering the port-Hamiltonian structure for an arbitrary system of differential equations. We complement our previous study on this topic by explaining the choice of machine learning algorithms and discussing some details of their application. We also consider the possibility provided by this approach for a potentially new definition of canonical forms and classification of systems of differential equations.

Abstract

Laurent solutions of systems of linear ordinary differential equations with truncated power series as coefficients are considered. The Laurent series in the solutions are also truncated. As a means for constructing such solutions, induced recurrent systems are used; earlier, an algorithm for the case when the induced recurrent system has a nonsingular leading matrix was proposed. For the series in solutions, this algorithm finds the maximum possible number of terms that are invariant with respect to any prolongation of the truncated coefficients of the original system. Results on extending the applicability of the earlier proposed algorithm to the case when the leading matrix is singular using the EG-elimination algorithm as an auxiliary tool. An implementation of the proposed algorithm in the form of a Maple procedure is given and examples of its use are presented.

Abstract

Code comments are an essential part of software documentation. Many software projects suffer from the problem of low-quality comments that are often produced by copy-paste. In case of similar methods, classes, etc. copy-pasted comments with minor modifications are justified. However, in many cases this approach leads to degraded documentation quality and, subsequently, to problematic maintenance and development of the project. In this study, we address the problem of near-duplicate code comments detection, which can potentially improve software documentation. We have conducted a thorough evaluation of traditional string similarity metrics and modern machine learning methods. In our experiment, we use a collection of Javadoc comments from four industrial open-source Java projects. We have found out that LCS (Longest Common Subsequence) is the best similarity algorithm taking into account both quality (Precision 94%, Recall 74%) and performance.

Abstract

This paper considers the problem of constructing compartmental models of dynamic systems by using a software package for symbolic calculation written in Julia. The software package is aimed at unifying the formalized construction of compartmental models, taking into account the meaningful description of possible interactions among compartments and the influence of various factors on the evolution of systems. An approach to the development of the instrumental and methodological basis for modeling the dynamic systems the behavior of which can be described by one-step processes is developed. The proposed software package enables the symbolic representation of the differential equations of the model in both stochastic and deterministic cases. It is implemented in Julia and uses the Julia Symbolics computer algebra library. A comparison between the Julia Symbolics tools and some other computer algebra systems is carried out. The application of the developed software package to a compartmental model is considered. The results can be used to solve problems of constructing and studying dynamic models in natural sciences that are represented by one-step processes.

Abstract

One of the basic aspects of information flow control in applications is a security policy language. This language should allow one to define security policies for evaluation of environment elements in coherence with higher-level access control rules. Hence, the language is expected to be flexible because there may be different access control paradigms (mandatory, role-based, etc.) implemented at the system level. The application may also have its own specific restrictions. Finally, it is also desirable that the language support declassification (controlled release of information) during computations. Paralocks is one of such languages. This research is devoted to the logical semantics of a modified version of Paralocks implemented in TLA+. Paralocks represents a language basis for the PLIF information flow control platform, which is developed with author’s participation for the analysis of PL/SQL program blocks. It includes proofs of the partial order and lattice defined on a set of security policy expressions.

Abstract

Topology synthesis in integrated design of wireless communication networks is considered. An iterative method has been developed for placing base stations of a broadband network along extended transportation routes. The problem of base station placement is formulated as an extremal problem on a finite set in the form of a special combinatorial model. An algorithm of the branch and bound method (BBM) has been developed to solve this problem. This algorithm serves as the basis for finding a sequence of best variants for the placement of base stations. Numerical calculations confirming the efficiency of the proposed algorithm are described.

Abstract

One of the open problems in modern control theory is synthesis of adaptive control for nonlinear systems with parametric uncertainty and analysis of stability of the corresponding closed-loop system. Fuzzy logic is one of the approaches that can take into account nonlinearity and uncertainty of the plant. Affine systems constitute a class of nonlinear systems often used to solve various practical problems. For this class, there are a number of methods for synthesis of controllers, in particular, a method based on the matrix Riccati equation with state-dependent coefficients. In this paper, for a given class of nonlinear systems, an adaptation mechanism of a neuro-fuzzy controller that approximates the control synthesized by the SDRE method is used for the first time. The main contribution of this work is the architecture of the neuro-fuzzy network and methods for its initialization. The proposed approach is applied to the model of a two-link manipulator with uncertain coefficients. The conducted numerical experiments demonstrate the effectiveness of the synthesized control in terms of the selected quality criteria.

Abstract

There is a wide range of fuzzing techniques for security assurance. Communication protocols and programs accepting complex structured data, including compilers, can be efficiently tested with a corresponding fuzzing approach. The main advantage of the fuzzing is actual data, which demonstrates the defects of the target software. The performance of fuzzing primarily depends on the quality of generated data. Existing fuzzing tools provide a fixed set of data generation algorithms, which doesn’t consider the specifics of the target program. There are several scenarios when the performance of the fuzzing may suffer. The target may execute different parts of the code based on a comparison of the offsets of the input data with some constant value. For such cases, random mutations will invalidate input data and lead to lower code coverage.

In this paper, we present a new approach for effective input data generation. We use static analysis to extract information regarding the input data offsets’ comparisons with constant values. Then we use this information during input data generation. Experimental evaluation of the developed method on several projects proves the efficiency of the developed method. Our approach allowed up to 91% increase in the number of executed paths for the same execution count.