Software Optimisation, Learning and Analytics Research

SOLAR is a group of researchers working on software engineering problems at the interface of software optimisation, machine/evolutionary learning and analytics.
The group currently consists of 15 members and is led by Prof Federica Sarro at University College London (UCL).
Our research work has obtained several international awards and generous funding. We have collaborated with several other researchers world-wide and also software companies, including Facebook and Google.
In SOLAR we promote and embrace open science, and thus we strive to share our publications, data, tools, and models inside and outside our group. You can find the presentations of some of our work on our YouTube channel.

Accepted Papers @IEEE TSE'20

Learning From Mistakes: Machine Learning Enhanced Human Expert Effort Estimates by Sarro et al.

Automatic Testing and Improvement of Machine Translation by Zhang et al.

Accepted Papers @ESEC/FSE'20

Cost Measures Matter for Mutation Testing Study Validity by Guizzo et al.

A Framework for Evaluating UI Test Reuse by Zhao et al.

Accepted Papers @GECCO'20

Optimising Word Embeddings With Search-Based Approaches by Hort & Sarro

A New Approach to Distribute MOEA Pareto Front Computation by Sarro et al.

Accepted Papers @ICSE'20

Automatic Testing and Improvement of Machine Translation by Zhang et al.