activity
20202026
most citedUsing Source Code Density to Improve the Accuracy of Automatic Commit Classification into Maintenance Activities

21 citations · 21 across the 3 of their papers we have counts for

collaborators

5 papers

cs.SE2026

When Does the Dependency Graph Help Code-to-Architecture Mapping?

Rakhshanda Jabeen, Morgan Ericsson, Jonas Nordqvist +1

Architectural technical debt arises when a system's implementation drifts from its inten ded modular decomposition, while the mapping between source files and architectural modu le…

cs.DC2026

Fine-grained Computation-Communication Overlap via Tile-level Signaling and Scheduling for Mixture-of-Experts

Minyu Cui, Anna Wingkvist, Morgan Ericsson

Mixture-of-Experts (MoE) architectures increase model capacity without proportionally increasing computation cost and have become a key building block for scaling large language mo…

cs.LG2021

Aggregation as Unsupervised Learning and its Evaluation

Maria Ulan, Welf Löwe, Morgan Ericsson +1

Regression uses supervised machine learning to find a model that combines several independent variables to predict a dependent variable based on ground truth (labeled) data, i.e.,…

cs.SE2021

To Automatically Map Source Code Entities to Architectural Modules with Naive Bayes

Tobias Olsson, Morgan Ericsson, Anna Wingkvist

Background: The process of mapping a source code entity onto an architectural module is to a large degree a manual task. Automating this process could increase the use of static ar…

cs.SE2020★ 21 cited

Using Source Code Density to Improve the Accuracy of Automatic Commit Classification into Maintenance Activities

Sebastian Hönel, Morgan Ericsson, Welf Löwe +1

Source code is changed for a reason, e.g., to adapt, correct, or adapt it. This reason can provide valuable insight into the development process but is rarely explicitly documented…