14 citations · 14 across the 5 of their papers we have counts for
5 papers
On the experiences of adopting automated data validation in an industrial machine learning project
Lucy Ellen Lwakatare, Ellinor Rånge, Ivica Crnkovic +1
Background: Data errors are a common challenge in machine learning (ML) projects and generally cause significant performance degradation in ML-enabled software systems. To ensure e…
HPM-Frame: A Decision Framework for Executing Software on Heterogeneous Platforms
Hugo Andrade, Ola Benderius, Christian Berger +2
Heterogeneous computing is one of the most important computational solutions to meet rapidly increasing demands on system performance. It typically allows the main flow of applicat…
Refactoring Software in the Automotive Domain for Execution on Heterogeneous Platforms
Hugo Andrade, Ivica Crnkovic, Jan Bosch
The most important way to achieve higher performance in computer systems is through heterogeneous computing, i.e., by adopting hardware platforms containing more than one type of p…
Engineering AI Systems: A Research Agenda
Jan Bosch, Ivica Crnkovic, Helena Holmström Olsson
Artificial intelligence (AI) and machine learning (ML) are increasingly broadly adopted in industry, However, based on well over a dozen case studies, we have learned that deployin…
A Review on Software Architectures for Heterogeneous Platforms
Hugo Andrade, Ivica Crnkovic
The increasing demands for computing performance have been a reality regardless of the requirements for smaller and more energy efficient devices. Throughout the years, the strateg…