Education

We are offering a series of projects under the umbrella of mining cloud cost awareness, that is, of software developers being aware of the costs of deploying and operating cloud-based software.

This project aims to investigate what is the environmental footprint of training and using chatbots.

We designed this project to help identify sustainability dimensions in the Stack Overflow posts to create a dataset containing sustainability-related posts. This will help researchers further work on sustainability using the dataset.

Determining Irrigation Events in collaboration with CropX

LabeBook is an integrative platform in the field of experimental science. The objective of this project is to develop a test environment to test its key functionalities

This project is about software development,and it will be run in collaboration with Klippa Groningen. The objective is to develop a novel approach to add components into the Klippa frontend

Klippa OCR preprocessing features

The goal of this project is to analyse how developers document SATD in non-code artefacts such as emails or issue tracking systems. The objective is to answer questions like "Do developers know beforehand what changes have to be made" and "Do initially proposed changes align with the actual changes?".

The goal of this project is to create a machine learning based system which can help determining whether a given fix for an SATD issue is actually correct. The project will involve creating an extended dataset of SATD items reported in issue tracking systems, together with the commits fixing the reported SATD items. This dataset will then be used to develop a machine learning model. The created model will enable more extensive collection of correct SATD fixes for use in future research.

This project offers interesting and challenging opportunities at the intersection of software engineering and artificial intelligence.

Join us in understanding the many ways in which development activities are unfair, the extent of the problem, and solutions to mitigate it. There are many interesting research problems here that will need software engineering and artificial intelligence-based solutions.

This project involves the identification of issues in global teams and/or ways to solve the problems experienced by global developers.

This project offers interesting and challenging opportunities at the intersection of software engineering and artificial intelligence.

This thesis will look into the unsupervised Anomaly Detection (AD) solutions in the DevOps CI/CD pipeline of SIG.

This project aims to improve code velocity at Mozilla Foundations. This project is in collaboration with Marco Castelluccio from Mozilla Foundations.

This thesis will generate a code for medium-size, preferably larger, software projects using LLMs. It will also assess the quality of the code generated using LLMs. This project is in collaboration with the Software Improvement Group (SIG) from Amsterdam.

What is readable software? How do you write more readable software? This project is in collaboration with Prof. Rui Abreu, a research software engineer with Meta.

This project offers interesting and challenging opportunities at the intersection of software engineering and artificial intelligence.

understanding how our quest for speed and quality drives opportunities away.

The vision of this project is to measure how software development is changing in current times.

conduct a comprehensive literature review on fairness in software development.

This project examines how disabled software developers are portrayed in the media.

The goal of this project is to explore how Rascal can support the definition of domain-specific spreadsheet languages.

The goal of this project is provide an M3 bridge to the Ethereum Solidity language. This will enable analysis and reverse engineering of Smart Contracts running on the Ethereum blockchain.

The goal of this project is to investigate how to embed Web-based diagram editor frameworks into the Salix model for defining UIs.

In this project the goal is to obtain a high quality Rascal grammar from the Swift language reference, in a (semi-)automatic, traceable way.

Some time ago, Nick Szabo wrote an essay exploring how a language for smart contracts could look like. The goal of this project is to go one step further to define a proper semantics and implementation of a language like this.

CodeBuff has been implemented in the context of the ANTLR parse generator, and uses its internal parse tree data structures for learning and formatting. We're interested in transferring CodeBuff to the context of the Rascal language workbench.

This thesis will fine-tune a small language model (SLM) for a specific software engineering task and evaluate its performance. The project will also investigate methods to correct or "unlearn" model misconceptions and adapt it for domain-specific tasks.

Investigate how the application of different design patterns (e.g., Singleton, Factory Method) impacts software maintainability in real-world projects. The study will involve analyzing open-source repositories to measure metrics such as cyclomatic complexity, code readability, and bug frequency.

Develop an AI-based tool that suggests and automates refactoring in Java projects. The focus will be on improving code smells like long methods or God classes while evaluating the tool’s effectiveness in reducing technical debt.

Build a graph-based model for detecting semantic code clones by leveraging program structure and control flow information. The project will evaluate the performance of Graph Neural Networks (GNNs) on benchmark datasets.

Develop a model that combines source code and abstract syntax tree (AST) embeddings for better downstream task performance, such as code summarization or classification. The project will compare its results against existing single-modal approaches.