91 citations · 250 across the 37 of their papers we have counts for
8 papers · 1 filter
Harnessing Pre-trained Generalist Agents for Software Engineering Tasks
Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh
Nowadays, we are witnessing an increasing adoption of Artificial Intelligence (AI) to develop techniques aimed at improving the reliability, effectiveness, and overall quality of s…
Common Challenges of Deep Reinforcement Learning Applications Development: An Empirical Study
Mohammad Mehdi Morovati, Florian Tambon, Mina Taraghi +2
Machine Learning (ML) is increasingly being adopted in different industries. Deep Reinforcement Learning (DRL) is a subdomain of ML used to produce intelligent agents. Despite rece…
Data Cleaning and Machine Learning: A Systematic Literature Review
Pierre-Olivier Côté, Amin Nikanjam, Nafisa Ahmed +2
Context: Machine Learning (ML) is integrated into a growing number of systems for various applications. Because the performance of an ML model is highly dependent on the quality of…
Effective Test Generation Using Pre-trained Large Language Models and Mutation Testing
Arghavan Moradi Dakhel, Amin Nikanjam, Vahid Majdinasab +2
One of the critical phases in software development is software testing. Testing helps with identifying potential bugs and reducing maintenance costs. The goal of automated test gen…
Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges
Ahmed Haj Yahmed, Altaf Allah Abbassi, Amin Nikanjam +2
Deep reinforcement learning (DRL), leveraging Deep Learning (DL) in reinforcement learning, has shown significant potential in achieving human-level autonomy in a wide range of dom…
Bug Characterization in Machine Learning-based Systems
Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon +3
Rapid growth of applying Machine Learning (ML) in different domains, especially in safety-critical areas, increases the need for reliable ML components, i.e., a software component…
Quality Issues in Machine Learning Software Systems
Pierre-Olivier Côté, Amin Nikanjam, Rached Bouchoucha +3
Context: An increasing demand is observed in various domains to employ Machine Learning (ML) for solving complex problems. ML models are implemented as software components and depl…
Mutation Testing of Deep Reinforcement Learning Based on Real Faults
Florian Tambon, Vahid Majdinasab, Amin Nikanjam +2
Testing Deep Learning (DL) systems is a complex task as they do not behave like traditional systems would, notably because of their stochastic nature. Nonetheless, being able to ad…