José Miguel Rojas

School of Computer Science

University of Sheffield

Sheffield, UK

I am a Lecturer (Assistant Professor) in Software Testing at the School of Computer Science, University of Sheffield.

Previously, I was a Lecturer in the Department of Informatics at the University of Leicester. Before that, I was a Research Associate in Software Testing in the Verification and Testing group at Sheffield, working with Prof Gordon Fraser.

I completed my PhD in Computer Science at the Technical University of Madrid (UPM), in the COSTA Group, supervised by Elvira Albert and Miguel Gómez-Zamalloa.

My research interests lie in automated software engineering, with a focus on search-based unit test generation, system-level testing for eXtended Reality (XR) software, and causality testing in smart manufacturing. Past work includes bio-inspired computational devices, constraint logic programming, and software static analysis and symbolic execution.

Selected Publications

ASE

Software Testing for Extended Reality Applications: A Systematic Mapping Study

Ruizhen Gu, José Miguel Rojas, and Donghwan Shin

Automated Software Engineering (ASE), 2025

DOI
ICSME

Private-Keep Out? Understanding How Developers Account for Code Visibility in Unit Testing

Muhammad Firhard Roslan, José Miguel Rojas, and Phil McMinn

In 2024 IEEE International Conference on Software Maintenance and Evolution (ICSME), 2024

DOI
AST

On the feasibility and challenges of synthesizing executable Espresso tests

Iván Arcuschin Moreno, Juan Pablo Galeotti, Christian Ciccaroni, and 1 more author

In IEEE/ACM International Conference on Automation of Software Test, AST@ICSE 2022, 2022

DOI
ICSE

Code Defenders: Crowdsourcing Effective Tests and Subtle Mutants with a Mutation Testing Game

José Miguel Rojas, Thomas White, Benjamin Clegg, and 1 more author

In Int. Conference on Software Engineering (ICSE), 2017

AWARD Abs DOI

ACM Distinguished Paper Award

Writing good software tests is difficult and not every developer’s favorite occupation. Mutation testing aims to help by seeding artificial faults (mutants) that good tests should identify, and test generation tools help by providing automatically generated tests. However, mutation tools tend to produce huge numbers of mutants, many of which are trivial, redundant, or semantically equivalent to the original program; automated test generation tools tend to produce tests that achieve good code coverage, but are otherwise weak and have no clear purpose. In this paper, we present an approach based on gamification and crowdsourcing to produce better software tests and mutants: The Code Defenders web-based game lets teams of players compete over a program, where attackers try to create subtle mutants, which the defenders try to counter by writing strong tests. Experiments in controlled and crowdsourced scenarios reveal that writing tests as part of the game is more enjoyable, and that playing Code Defenders results in stronger test suites and mutants than those produced by automated tools.