Opportunistic Research
I went into software engineering (SE) simply because I ended up in an SE lab during my PhD. But really, it could have been otherwise. I didn't have any particular calling for this subject. In fact, I took no SE courses before working on my PhD. It did not even exist in the French CS curriculum. We only had programming language courses at the time.
I also started using Machine Learning (ML) very early on because I was working on NASA software development data. I recall people scolding me, telling me ML was not a serious area of AI. My decisions were driven by the need to analyze large, unstructured datasets.
In SE, I ended up spending most of my time on Automated Testing (including fault localisation and repair, AI and security aspects) and Requirements Engineering (including legal aspects), often using AI, simply because I liked working with industry, and it was way easier to convince them to work on these topics. The rest of my work was about real-time schedulability analysis, quality assurance, and model-driven engineering, primarily during the early stages of my career.
True, this was a somewhat opportunistic way to choose my research focus and pursuits. However, I honestly didn't mind. I believe that almost anything can be interesting if you put your mind to it. What really mattered to me was practical impact.
Lionel C. Briand is professor of software engineering and has shared appointments between (1) The University of Ottawa, Canada, where he holds a Canada Research Chair (Tier 1) and (2) Ireland's Lero Centre for Software Research, where he holds the position of Director. In collaboration with colleagues, over 30 years, he has run many collaborative research projects with companies in the automotive, satellite, aerospace, energy, financial, and legal domains. Lionel has held various engineering, academic, and leading positions in seven countries. He was one of the founders of the ICST conference (IEEE Int. Conf. on Software Testing, Verification, and Validation, a CORE A event) and its first general chair. He was also EiC of Empirical Software Engineering (Springer) for 13 years and led, in collaboration with first Victor Basili and then Tom Zimmermann, the journal to the top tier of the very best publication venues in software engineering.
Lionel was elevated to the grades of IEEE Fellow and ACM Fellow for his work on software testing and verification. He was granted the IEEE Computer Society Harlan Mills award, the ACM SIGSOFT outstanding research award, and the IEEE Reliability Society engineer-of-the-year award, respectively in 2012, 2022, and 2013. He received an ERC Advanced grant in 2016 — on the topic of modelling and testing cyber-physical systems — which is the most prestigious individual research award in the European Union. In 2023, he was elevated to the rank of fellow of the Academy of Science, Royal Society of Canada. He currently holds a Canada Research Chair (Tier 1) on "Intelligent Software Dependability and Compliance". His research interests include: Trustworthy AI, software testing and verification, applications of AI in software engineering, model-driven software development, requirements engineering, and empirical software engineering.