91 citations · 250 across the 37 of their papers we have counts for
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Quality issues in Machine Learning Software Systems
Pierre-Olivier Côté, Amin Nikanjam, Rached Bouchoucha +1
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…
A Comparison of Reinforcement Learning Frameworks for Software Testing Tasks
Paulina Stevia Nouwou Mindom, Amin Nikanjam, Foutse Khomh
Software testing activities scrutinize the artifacts and the behavior of a software product to find possible defects and ensure that the product meets its expected requirements. Re…
An Empirical Study of Challenges in Converting Deep Learning Models
Moses Openja, Amin Nikanjam, Ahmed Haj Yahmed +3
There is an increase in deploying Deep Learning (DL)-based software systems in real-world applications. Usually DL models are developed and trained using DL frameworks that have th…
GitHub Copilot AI pair programmer: Asset or Liability?
Arghavan Moradi Dakhel, Vahid Majdinasab, Amin Nikanjam +4
Automatic program synthesis is a long-lasting dream in software engineering. Recently, a promising Deep Learning (DL) based solution, called Copilot, has been proposed by OpenAI an…
Bugs in Machine Learning-based Systems: A Faultload Benchmark
Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh +2
The rapid escalation of applying Machine Learning (ML) in various domains has led to paying more attention to the quality of ML components. There is then a growth of techniques and…