Building Secure and High-Performance Software Systems

10.1142/7069 ◽  
2022 ◽  
Author(s):  
Issa Traore ◽  
Ahmed Awad E Ahmed
Author(s):  
Hitesh Yadav ◽  
Rita Chhikara ◽  
Charan Kumari

Background: Software Product Line is the group of multiple software systems which share the similar set of features with multiple variants. Feature model is used to capture and organize features used in different multiple organization. Objective: The objective of this research article is to obtain an optimized subset of features which are capable of providing high performance. Methods: In order to achieve the desired objective, two methods have been proposed. a) An improved objective function which is used to compute the contribution of each feature with weight based methodology. b) A hybrid model is employed to optimize the Software Product Line problem. Results: Feature sets varying in size from 100 to 1000 have been used to compute the performance of the Software Product Line. Conclusion: The results shows that proposed hybrid model outperforms the state of art metaheuristic algorithms.


Author(s):  
E. A. Skornyakova ◽  
V. M. Vasyukov ◽  
V. S. Sulaberidze

The authors analysed the most popular production planning and scheduling software systems. Their main disadvantage is that they lack lean manufacturing tools. There exists a demand for client-oriented systems based on lean principles. The paper describes a unique algorithm for computing the optimum takt time, which forms the basis of the scheduling system developed by the authors. We present methods of algorithmising the scheduling process and results of generating schedules using several algorithms


Proceedings ◽  
2019 ◽  
Vol 46 (1) ◽  
pp. 18
Author(s):  
Habib Izadkhah ◽  
Mahjoubeh Tajgardan

Software clustering is usually used for program comprehension. Since it is considered to be the most crucial NP-complete problem, several genetic algorithms have been proposed to solve this problem. In the literature, there exist some objective functions (i.e., fitness functions) which are used by genetic algorithms for clustering. These objective functions determine the quality of each clustering obtained in the evolutionary process of the genetic algorithm in terms of cohesion and coupling. The major drawbacks of these objective functions are the inability to (1) consider utility artifacts, and (2) to apply to another software graph such as artifact feature dependency graph. To overcome the existing objective functions’ limitations, this paper presents a new objective function. The new objective function is based on information theory, aiming to produce a clustering in which information loss is minimized. For applying the new proposed objective function, we have developed a genetic algorithm aiming to maximize the proposed objective function. The proposed genetic algorithm, named ILOF, has been compared to that of some other well-known genetic algorithms. The results obtained confirm the high performance of the proposed algorithm in solving nine software systems. The performance achieved is quite satisfactory and promising for the tested benchmarks.


The remarkable progress in the architecture, speed and capacity of computer hardware continues to drive the development of quantum mechanical methods, thus allowing calculations on increasingly complex systems. Using high-end computers, accurate quantum mechanical all-electron studies are now possible for solids such as transition metal compounds containing about fifty atoms per unit cell. Pseudo-potential plane-wave methods are being applied to unit cells with 400 silicon atoms, and organic molecules consisting of over 100 atoms have become tractable using ab initio methods. Smaller, yet still useful calculations can be carried out on workstations. The combination of graphics workstations and high-performance supercomputers, integrated in tightly coupled heterogeneous networks, has allowed the design of software systems with unprecedented convenience and visualization capabilities. Despite this progress, however, there is still an urgent need for new quantum mechanical methods which converge systematically to the exact solution of Schrodinger’s equation while maintaining a reasonable scaling of the computational effort with the system size.


2021 ◽  
Vol 33 (5) ◽  
pp. 237-248
Author(s):  
Ivan Alekseevich Amelyushkin ◽  
Maksim Aleksandrovich Kudrov ◽  
Alexey Olegovich Morozov ◽  
Andrey Sergeevich Shcheglov

The study of aircraft icing modes, in which it is necessary to take into account the effect of droplet crushing, is of great interest in calculating the icing of aircraft, optimizing the hydrophobic and anti-icing properties of coatings, and is relevant in a number of other practical applications. Of great practical importance is the development of high-performance methods for calculating the interaction of aerosol flows with a solid. This work is devoted to the development of a model of particle dynamics, as well as a model of fragmentation of supercooled droplets of an aerosol flow during its interaction with the surface of a streamlined body. Developed physical and mathematical models can be used in software systems for numerical modeling of aircraft icing.


2000 ◽  
Vol 4 (4) ◽  
pp. 97-109
Author(s):  
Li Hongbing ◽  
Meng Bo ◽  
Chen Shifu

The design and construction of virtual reality environments involve technologies such as computer graphics, image processing, pattern recognition, intelligent interface, artificial intelligence, voice recognition, network, parallel processing, and high-performance computing. Some researchers insist that object-oriented and agent-oriented technologies are fundamental for virtual reality system design. This paper applies artificial intelligence to the design of virtual reality systems. Agents are constructed by using object-oriented methods and a set of underlying computing models, such as neural networks, genetic algorithms, expert systems, and plan managers. Some object-oriented frameworks of these computing models are presented to illustrate this approach. The example of a spaceship game will illustrate interactions among environments, agents, and underlying computing models. The approach and reusable class library presented herein can be applied to various virtual reality environment simulations and intelligent applications.


Author(s):  
Randall Bramley ◽  
Rob Armstrong ◽  
Lois McInnes ◽  
Matt Sottile

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