Searched for: department%3A%22Software%255C+Technology%22
(1 - 11 of 11)
document
Poenaru-Olaru, L. (author), Sallou, J. (author), Cruz, Luis (author), Rellermeyer, Jan S. (author), van Deursen, A. (author)
Deployed machine learning systems often suffer from accuracy degradation over time generated by constant data shifts, also known as concept drift. Therefore, these systems require regular maintenance, in which the machine learning model needs to be adapted to concept drift. The literature presents plenty of model adaptation techniques. The...
conference paper 2023
document
Shome, A. (author), Cruz, Luis (author), van Deursen, A. (author)
Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a human-in-the-loop approach. Besides writing tests for the code base, bulk of the evaluation requires application of domain...
conference paper 2023
document
Poenaru-Olaru, L. (author), Cruz, Luis (author), Rellermeyer, Jan S. (author), van Deursen, A. (author)
AIOps solutions enable faster discovery of failures in operational large-scale systems through machine learning models trained on operation data. These models become outdated during the occurrence of concept drift, a term used to describe shifts in data distributions. In operation data concept drift is inevitable and it impacts the...
conference paper 2023
document
Yarally, Tim (author), Cruz, Luis (author), Feitosa, Daniel (author), Sallou, J. (author), van Deursen, A. (author)
Modern AI practices all strive towards the same goal: better results. In the context of deep learning, the term "results"often refers to the achieved accuracy on a competitive problem set. In this paper, we adopt an idea from the emerging field of Green AI to consider energy consumption as a metric of equal importance to accuracy and to...
conference paper 2023
document
Shome, A. (author), Cruz, Luis (author), van Deursen, A. (author)
The adoption of Artificial Intelligence (AI) in high-stakes domains such as healthcare, wildlife preservation, autonomous driving and criminal justice system calls for a data-centric approach to AI. Data scientists spend the majority of their time studying and wrangling the data, yet tools to aid them with data analysis are lacking. This...
conference paper 2022
document
Van Oort, Bart (author), Cruz, Luis (author), Loni, Babak (author), van Deursen, A. (author)
Machine Learning (ML) projects incur novel challenges in their development and productionisation over traditional software applications, though established principles and best practices in ensuring the project's software quality still apply. While using static analysis to catch code smells has been shown to improve software quality attributes...
conference paper 2022
document
Zhang, H. (author), Cruz, Luis (author), van Deursen, A. (author)
The popularity of machine learning has wildly expanded in recent years. Machine learning techniques have been heatedly studied in academia and applied in the industry to create business value. However, there is a lack of guidelines for code quality in machine learning applications. In particular, code smells have rarely been studied in this...
conference paper 2022
document
Chuang, Ching-Chi (author), Cruz, Luis (author), van Dalen, Robbert (author), Mikovski, Vladimir (author), van Deursen, A. (author)
When developing and maintaining large software systems, a great deal of effort goes into dependency management. During the whole lifecycle of a software project, the set of dependencies keeps changing to accommodate the addition of new features or changes in the running environment. Package management tools are quite popular to automate this...
conference paper 2022
document
Poenaru-Olaru, L. (author), Cruz, Luis (author), van Deursen, A. (author), Rellermeyer, Jan S. (author)
As machine learning models increasingly replace traditional business logic in the production system, their lifecycle management is becoming a significant concern. Once deployed into production, the machine learning models are constantly evaluated on new streaming data. Given the continuous data flow, shifting data, also known as concept drift,...
conference paper 2022
document
van Oort, B. (author), Cruz, Luis (author), Aniche, MaurĂ­cio (author), van Deursen, A. (author)
Artificial Intelligence (AI) and Machine Learning (ML) are pervasive in the current computer science landscape. Yet, there still exists a lack of software engineering experience and best practices in this field. One such best practice, static code analysis, can be used to find code smells, i.e., (potential) defects in the source code,...
conference paper 2021
document
Haakman, Mark (author), Cruz, Luis (author), Huijgens, H.K.M. (author), van Deursen, A. (author)
Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components. Thus, the same development processes and standards in software engineering ought to be complied in artificial intelligence systems. This study aims to understand the...
journal article 2021
Searched for: department%3A%22Software%255C+Technology%22
(1 - 11 of 11)