efficient algorithms
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2022 ◽  
Vol 44 (1) ◽  
pp. 1-37
Author(s):  
Martin Hecker ◽  
Simon Bischof ◽  
Gregor Snelting

We present efficient algorithms for time-sensitive control dependencies (CDs). If statement y is time-sensitively control dependent on statement x , then x decides not only whether y is executed but also how many timesteps after x . If y is not standard control dependent on x , but time-sensitively control dependent, then y will always be executed after x , but the execution time between x and y varies. This allows us to discover, e.g., timing leaks in security-critical software. We systematically develop properties and algorithms for time-sensitive CDs, as well as for nontermination-sensitive CDs. These work not only for standard control flow graphs (CFGs) but also for CFGs lacking a unique exit node (e.g., reactive systems). We show that Cytron’s efficient algorithm for dominance frontiers [ 10 ] can be generalized to allow efficient computation not just of classical CDs but also of time-sensitive and nontermination-sensitive CDs. We then use time-sensitive CDs and time-sensitive slicing to discover cache timing leaks in an AES implementation. Performance measurements demonstrate scalability of the approach.


2022 ◽  
Vol 18 (1) ◽  
pp. 1-16
Author(s):  
Alessandra Graf ◽  
David G. Harris ◽  
Penny Haxell

An independent transversal (IT) in a graph with a given vertex partition is an independent set consisting of one vertex in each partition class. Several sufficient conditions are known for the existence of an IT in a given graph and vertex partition, which have been used over the years to solve many combinatorial problems. Some of these IT existence theorems have algorithmic proofs, but there remains a gap between the best existential bounds and the bounds obtainable by efficient algorithms. Recently, Graf and Haxell (2018) described a new (deterministic) algorithm that asymptotically closes this gap, but there are limitations on its applicability. In this article, we develop a randomized algorithm that is much more widely applicable, and demonstrate its use by giving efficient algorithms for two problems concerning the strong chromatic number of graphs.


Author(s):  
Marcelo Manteigas ◽  
António Andrade-Campos ◽  
André Antunes ◽  
Bernardete Coelho

Author(s):  
И.С. Бондарчук ◽  
С.С. Титов ◽  
С.С. Бондарчук

В работе предлагаются два новых эффективных алгоритма, реализованных коротким программным кодом в MS Excel, предназначенных для идентификации и характеризации размеров нано– и микропорошков частиц в виде обобщенного гамма или логнормального распределений по данным опытных гистограмм. Предлагаемый метод представляет собой новый и достаточно общий подход к решению обратных задач идентификации параметров дифференциальных функций распределения по экспериментальным данным на основе на минимизации функционала, представляющего собой коэффициент детерминации.Алгоритм реализован формулами (менее 10) наиболее распространенного инструментария (электронных таблиц MS Excel без использования макросов), позволяющего исследователям, не обладающими навыками профессиональных программистов, простоту проверки и воспроизведения представленного материала, а также возможность модификации кода для решения более широкого круга задач. Текст статьи и комментарии на рабочих листах скриншотов представляют собой готовые инструкции по решению задач идентификация функций распределения и характеризации размеров нано– и микропорошков. The paper proposes two new efficient algorithms, implemented by a short program code in MS Excel, designed to identify and characterize the sizes of nano- and micropowders of particles in the form of generalized gamma or lognormal distributions according to experimental histograms. The proposed method is a new general approach to solving inverse problems of identifying the parameters of differential distribution functions from experimental data based on minimizing the functional that is the coefficient of determination.The algorithm is implemented with formulas (less than 10) of the most common tools (MS Excel spreadsheets without the use of macros), which allow researchers without the skills of professional programmers to easily check and reproduce the presented material, as well as the ability to modify the code to solve a wider range of problems. The text of the article and comments on the worksheets of screenshots represent ready-made instructions for solving problems of identification of distribution functions and characterization of the sizes of nano- and micropowders.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Hristiyan Dimitrov ◽  
◽  
◽  

This paper presents modern AI applications using real life company projects, which try to solve problems related to the self-driving car industry, medicine and the overall quality of life. By utilizing big data, efficient algorithms and proper modelling, these projects make exceptional progress in their respective fields. The paper examines the underlying foundations of the projects and the challenges they face.


2021 ◽  
Author(s):  
Guido Governatori ◽  
Francesco Olivieri ◽  
Antonino Rotolo ◽  
Abdul Sattar ◽  
Matteo Cristani

This paper develops a new comprehensive computational framework for reasoning about private international law that encompasses the reasoning patterns modeled by previous works [3,8,9]. The framework is a multi-modal extension of [10] preserving some nice properties of the original system, including some efficient algorithms to compute the extensions of normative theories representing legal systems.


2021 ◽  
Vol 186 ◽  
pp. 115741
Author(s):  
Trinh D.D. Nguyen ◽  
Loan T.T. Nguyen ◽  
Lung Vu ◽  
Bay Vo ◽  
Witold Pedrycz

2021 ◽  
Vol 139 ◽  
pp. 143-165
Author(s):  
Daniel A. Melo Moreira ◽  
Karina Valdivia Delgado ◽  
Leliane Nunes de Barros ◽  
Denis Deratani Mauá

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