
Aleksandar ChakarovPhase Change Software LLC, Golden, CO, United States
Aleksandar Chakarov
Doctor of Philosophy in Computer Science, University of Colorado Boulder
About
17
Publications
2,308
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
577
Citations
Citations since 2017
Introduction
Publications
Publications (17)
We present lifestate rules--an approach for abstracting event-driven object protocols. Developing applications against event-driven software frameworks is notoriously difficult. One reason why is that to create functioning applications, developers must know about and understand the complex protocols that abstract the internal behavior of the framew...
We consider the problem of reasoning about the probability of assertion violations in straight-line, nonlinear computations involving uncertain quantities modeled as random variables. Such computations are quite common in many areas such as cyber-physical systems and numerical computation. Our approach extends probabilistic affine forms, an interva...
Martingale theory yields a powerful set of tools that have recently been used to prove quantitative properties of stochastic systems such as stochas-tic safety and qualitative properties such as almost sure termination. In this paper , we examine proof techniques for establishing almost sure persistence and recurrence properties of infinite-state d...
Unlike traditional programs (such as operating systems or word processors) which have large amounts of code, machine learning tasks use programs with relatively small amounts of code (written in machine learning libraries), but voluminous amounts of data. Just like developers of traditional programs debug errors in their code, developers of machine...
We present static analyses for probabilistic loops using expectation invariants. Probabilistic loops are imperative while-loops augmented with calls to random value generators. Whereas, traditional program analysis uses Floyd-Hoare style invariants to over-approximate the set of reachable states, our approach synthesizes invariant inequalities invo...
We present static analyses for probabilistic loops using expectation invariants. Probabilistic loops are imperative while-loops augmented with calls to random variable generators. Whereas, traditional program analysis uses Floyd-Hoare style invariants to over-approximate the set of reachable states, our approach synthesizes invariant inequalities i...
We present techniques for the analysis of infinite state probabilistic programs to synthesize probabilistic invariants and prove almost-sure termination. Our analysis is based on the notion of (super) martingales from probability theory. First, we define the concept of (super) martingales for loops in probabilistic programs. Next, we present the us...
We propose an approach for the static analysis of probabilistic programs that sense, manipulate, and control based on uncertain data. Examples include programs used in risk analysis, medical decision making and cyber-physical systems. Correctness properties of such programs take the form of queries that seek the probabilities of assertions over pro...
We propose an approach for the static analysis of probabilistic programs that sense, manipulate, and control based on uncertain data. Examples include programs used in risk analysis, medical decision making and cyber-physical systems. Correctness properties of such programs take the form of queries that seek the probabilities of assertions over pro...
In this paper, we present a promising approach to systematically testing graphical user interfaces (GUI) in a platform independent manner. Our framework uses standard computer vision techniques through a python-based scripting language (Sikuli script) to identify key graphical elements in the screen and automatically interact with these elements by...
Partial words are sequences over a finite alphabet that may contain some undefined positions called holes. We consider unavoidable sets of partial words of equal length. We compute the minimum number of holes in sets of size three over a binary alphabet (summed over all partial words in the sets). We also construct all sets that achieve this minimu...
Partial words are sequences over a finite alphabet that may contain wildcard symbols, called holes, which match, or are compatible with, all letters in the alphabet ((full) words are just partial words without holes). The subword complexity function of a partial word w over a finite alphabet A assigns to each positive integer, n, the number, pw(n),...
In this paper, we investigate formalisms for specifying periodic signals using time and frequency domain specifications along with algorithms for the signal recognition and generation problems for such specifications. The time domain specifications are in the form of hybrid automata whose continuous state variables generate the desired signals. The...
Partial words are sequences over a finite alphabet that may contain wildcard
symbols, called holes, which match or are compatible with all letters; partial
words without holes are said to be full words (or simply words). Given an
infinite partial word w, the number of distinct full words over the alphabet
that are compatible with factors of w of le...
Partial words are sequences over a finite alphabet that may contain some undefined positions called holes. In this paper,
we consider unavoidable sets of partial words of equal length. We compute the minimum number of holes in sets of size three
over a binary alphabet (summed over all partial words in the sets). We also construct all sets that achi...
This work presents a method for associating a class of constraint satisfaction problems to a three-dimensional knot. Given a knot, one can build a knot quandle, which is generally an infinite free algebra. The desired collection of problems is derived from the set of invariant relations over the knot quandle, applying theory that relates finite alg...