activity
20122020
most citedEffective Analysis of C Programs by Rewriting Variability

23 citations · 38 across the 7 of their papers we have counts for

collaborators

9 papers

cs.PL20201 cited

A Decision Tree Lifted Domain for Analyzing Program Families with Numerical Features (Extended Version)

Aleksandar S. Dimovski, Sven Apel, Axel Legay

Lifted (family-based) static analysis by abstract interpretation is capable of analyzing all variants of a program family simultaneously, in a single run without generating any of…

cs.LG2019

Prediction of Horizontal Data Partitioning Through Query Execution Cost Estimation

Nino Arsov, Goran Velinov, Aleksandar S. Dimovski +3

The excessively increased volume of data in modern data management systems demands an improved system performance, frequently provided by data distribution, system scalability and…

cs.PL20192 cited

Variability Abstraction and Refinement for Game-based Lifted Model Checking of full CTL (Extended Version)

Aleksandar S. Dimovski, Axel Legay, Andrzej Wasowski

Variability models allow effective building of many custom model variants for various configurations. Lifted model checking for a variability model is capable of verifying all its…

cs.PL2018

Verification of High-Level Transformations with Inductive Refinement Types

Ahmad Salim Al-Sibahi, Thomas P. Jensen, Aleksandar S. Dimovski +1

High-level transformation languages like Rascal include expressive features for manipulating large abstract syntax trees: first-class traversals, expressive pattern matching, backt…

cs.LO2018

Abstract Family-based Model Checking using Modal Featured Transition Systems: Preservation of CTL* (Extended Version)

Aleksandar S. Dimovski

Variational systems allow effective building of many custom variants by using features (configuration options) to mark the variable functionality. In many of the applications, thei…

cs.PL20176 cited

Probabilistic Analysis Based On Symbolic Game Semantics and Model Counting

Aleksandar S. Dimovski

Probabilistic program analysis aims to quantify the probability that a given program satisfies a required property. It has many potential applications, from program understanding a…