26 citations · 80 across the 14 of their papers we have counts for
15 papers
Black-Box Bug-Amplification for Multithreaded Software
Yeshayahu Weiss, Gal Amram, Achiya Elyasaf +3
Bugs, especially those in concurrent systems, are often hard to reproduce because they manifest only under rare conditions. Testers frequently encounter failures that occur only un…
A Behavior-Based Knowledge Representation Improves Prediction of Players' Moves in Chess by 25%
Benny Skidanov, Daniel Erbesfeld, Gera Weiss +1
Predicting player behavior in strategic games, especially complex ones like chess, presents a significant challenge. The difficulty arises from several factors. First, the sheer nu…
Deep Learning-Based Operators for Evolutionary Algorithms
Eliad Shem-Tov, Moshe Sipper, Achiya Elyasaf
We present two novel domain-independent genetic operators that harness the capabilities of deep learning: a crossover operator for genetic algorithms and a mutation operator for ge…
Keeping Behavioral Programs Alive: Specifying and Executing Liveness Requirements
Tom Yaacov, Achiya Elyasaf, Gera Weiss
One of the benefits of using executable specifications such as Behavioral Programming (BP) is the ability to align the system implementation with its requirements. This is facilita…
Evolving Assembly Code in an Adversarial Environment
Irina Maliukov, Gera Weiss, Oded Margalit +1
In this work, we evolve Assembly code for the CodeGuru competition. The goal is to create a survivor -- an Assembly program that runs the longest in shared memory, by resisting att…
Deep Neural Crossover
Eliad Shem-Tov, Achiya Elyasaf
We present a novel multi-parent crossover operator in genetic algorithms (GAs) called ``Deep Neural Crossover'' (DNC). Unlike conventional GA crossover operators that rely on a ran…
Fitness Approximation through Machine Learning
Itai Tzruia, Tomer Halperin, Moshe Sipper +1
We present a novel approach to performing fitness approximation in genetic algorithms (GAs) using machine-learning (ML) models, through dynamic adaptation to the evolutionary state…
Provengo: A Tool Suite for Scenario Driven Model-Based Testing
Michael Bar-Sinai, Achiya Elyasaf, Gera Weiss +1
We present Provengo, a comprehensive suite of tools designed to facilitate the implementation of Scenario-Driven Model-Based Testing (SDMBT), an innovative approach that utilizes s…
A Melting Pot of Evolution and Learning
Moshe Sipper, Achiya Elyasaf, Tomer Halperin +5
We survey eight recent works by our group, involving the successful blending of evolutionary algorithms with machine learning and deep learning: 1. Binary and Multinomial Classific…
EC-KitY: Evolutionary Computation Tool Kit in Python with Seamless Machine Learning Integration
Moshe Sipper, Tomer Halperin, Itai Tzruia +1
EC-KitY is a comprehensive Python library for doing evolutionary computation (EC), licensed under the BSD 3-Clause License, and compatible with scikit-learn. Designed with modern s…
What Petri Net Obliges Us to Say: Comparing Approaches for Behavior Composition
Achiya Elyasaf, Tom Yaacov, Gera Weiss
We identify and demonstrate a weakness of Petri Nets (PN) in specifying composite behavior of reactive systems. Specifically, we show how, when specifying multiple requirements in…
Scenario-Assisted Deep Reinforcement Learning
Raz Yerushalmi, Guy Amir, Achiya Elyasaf +3
Deep reinforcement learning has proven remarkably useful in training agents from unstructured data. However, the opacity of the produced agents makes it difficult to ensure that th…
Generalized Coverage Criteria for Combinatorial Sequence Testing
Achiya Elyasaf, Eitan Farchi, Oded Margalit +2
We present a new model-based approach for testing systems that use sequences of actions and assertions as test vectors. Our solution includes a method for quantifying testing quali…
Evolving Context-Aware Recommender Systems With Users in Mind
Amit Livne, Eliad Shem Tov, Adir Solomon +3
A context-aware recommender system (CARS) applies sensing and analysis of user context to provide personalized services. The contextual information can be driven from sensors in or…
Context-Oriented Behavioral Programming
Achiya Elyasaf
Modern systems require programmers to develop code that dynamically adapts to different contexts, leading to the evolution of new context-oriented programming languages. These lang…