61 citations · 225 across the 36 of their papers we have counts for
23 papers · 1 filter
Characterizing Feedback Statements in Machine Learning Jupyter Notebooks
Arumoy Shome, Lu\is Cruz, Diomidis Spinellis +1
Machine learning development in Jupyter notebooks is iterative and feedback-driven. Practitioners author statements that reveal information about program execution and use it to de…
"It Comes in Notebooks": Changes and Challenges when Operationalizing ML Prototypes
Arumoy Shome, Luís Cruz, Diomidis Spinellis +1
Machine learning practitioners commonly prototype models in computational notebooks before transitioning them to automated production systems. Despite its prevalence, the concrete…
Evaluating Non-English Developer Support in Machine Learning for Software Engineering
Jonathan Katzy, Yongcheng Huang, Gopal-Raj Panchu +5
Large Language Models are increasingly used in software engineering, but both code generation and its evaluation remain predominantly English-centric. This leaves a major gap in ou…
Learning from Change: Predictive Models for Incident Prevention in a Regulated IT Environment
Eileen Kapel, Jan Lennartz, Luis Cruz +2
Effective IT change management is important for businesses that depend on software and services, particularly in highly regulated sectors such as finance, where operational reliabi…
TreeRanker: Fast and Model-agnostic Ranking System for Code Suggestions in IDEs
Daniele Cipollone, Egor Bogomolov, Arie van Deursen +1
Token-level code completion is one of the most critical features in modern Integrated Development Environments (IDEs). It assists developers by suggesting relevant identifiers and…
Understanding Feedback Mechanisms in Machine Learning Jupyter Notebooks
Arumoy Shome, Luis Cruz, Diomidis Spinellis +1
The machine learning development lifecycle is characterized by iterative and exploratory processes that rely on feedback mechanisms to ensure data and model integrity. Despite the…
A Transformer-Based Approach for Smart Invocation of Automatic Code Completion
Aral de Moor, Arie van Deursen, Maliheh Izadi
Transformer-based language models are highly effective for code completion, with much research dedicated to enhancing the content of these completions. Despite their effectiveness,…
An Exploratory Investigation into Code License Infringements in Large Language Model Training Datasets
Jonathan Katzy, Răzvan-Mihai Popescu, Arie van Deursen +1
Does the training of large language models potentially infringe upon code licenses? Furthermore, are there any datasets available that can be safely used for training these models…
Language Models for Code Completion: A Practical Evaluation
Maliheh Izadi, Jonathan Katzy, Tim van Dam +3
Transformer-based language models for automatic code completion have shown great promise so far, yet the evaluation of these models rarely uses real data. This study provides both…
McUDI: Model-Centric Unsupervised Degradation Indicator for Failure Prediction AIOps Solutions
Lorena Poenaru-Olaru, Luis Cruz, Jan Rellermeyer +1
Due to the continuous change in operational data, AIOps solutions suffer from performance degradation over time. Although periodic retraining is the state-of-the-art technique to p…
Towards Automatic Translation of Machine Learning Visual Insights to Analytical Assertions
Arumoy Shome, Luis Cruz, Arie van Deursen
We present our vision for developing an automated tool capable of translating visual properties observed in Machine Learning (ML) visualisations into Python assertions. The tool ai…
Dynamic Prediction of Delays in Software Projects using Delay Patterns and Bayesian Modeling
Elvan Kula, Eric Greuter, Arie van Deursen +1
Modern agile software projects are subject to constant change, making it essential to re-asses overall delay risk throughout the project life cycle. Existing effort estimation mode…
On the Impact of Language Selection for Training and Evaluating Programming Language Models
Jonathan Katzy, Maliheh Izadi, Arie van Deursen
The recent advancements in Transformer-based Language Models have demonstrated significant potential in enhancing the multilingual capabilities of these models. The remarkable prog…
Towards Understanding Machine Learning Testing in Practise
Arumoy Shome, Luis Cruz, Arie van Deursen
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…
STACC: Code Comment Classification using SentenceTransformers
Ali Al-Kaswan, Maliheh Izadi, Arie van Deursen
Code comments are a key resource for information about software artefacts. Depending on the use case, only some types of comments are useful. Thus, automatic approaches to classify…
An Empirical Study on Data Leakage and Generalizability of Link Prediction Models for Issues and Commits
Maliheh Izadi, Pooya Rostami Mazrae, Tom Mens +1
To enhance documentation and maintenance practices, developers conventionally establish links between related software artifacts manually. Empirical research has revealed that deve…
Nalanda: A Socio-Technical Graph for Building Software Analytics Tools at Enterprise Scale
Chandra Maddila, Suhas Shanbhogue, Apoorva Agrawal +6
Software development is information-dense knowledge work that requires collaboration with other developers and awareness of artifacts such as work items, pull requests, and files.…
ConE: A Concurrent Edit Detection Tool for Large Scale Software Development
Chandra Maddila, Nachiappan Nagappan, Christian Bird +2
Modern, complex software systems are being continuously extended and adjusted. The developers responsible for this may come from different teams or organizations, and may be distri…
Nudge: Accelerating Overdue Pull Requests Towards Completion
Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal +3
Pull requests are a key part of the collaborative software development and code review process today. However, pull requests can also slow down the software development process whe…
AI Lifecycle Models Need To Be Revised. An Exploratory Study in Fintech
Mark Haakman, Luís Cruz, Hennie Huijgens +1
Tech-leading organizations are embracing the forthcoming artificial intelligence revolution. Intelligent systems are replacing and cooperating with traditional software components.…
Breviz: Visualizing Spreadsheets using Dataflow Diagrams
Felienne Hermans, Martin Pinzger, Arie van Deursen
Spreadsheets are used extensively in industry, often for business critical purposes. In previous work we have analyzed the information needs of spreadsheet professionals and addres…
An Architectural Style for Ajax
Ali Mesbah, Arie van Deursen
A new breed of web application, dubbed AJAX, is emerging in response to a limited degree of interactivity in large-grain stateless Web interactions. At the heart of this new approa…
A Systematic Aspect-Oriented Refactoring and Testing Strategy, and its Application to JHotDraw
Arie van Deursen, Marius Marin, Leon Moonen
Aspect oriented programming aims at achieving better modularization for a system's crosscutting concerns in order to improve its key quality attributes, such as evolvability and re…