On May 3, 2018 I gave an invited talk at the 9th Annual Graduate Student Research Conference at UOIT. The topic of my talk was “How to Succeed (and Fail) at Interdisciplinary Research.”
Interdisciplinary research is defined as research than involves multiple areas of knowledge and expertise.
As graduate students, researchers are often trained to develop expertise in only one specific area and those interested in interdisciplinary problems usually need to collaborate to be successful.
This week I gave a research seminar at Dalhousie University and at Mount Allison University on “Automating Software Development Using Artificial Intelligence (AI).” The intersection of AI and Software Engineering is an active research area and has lead to a number of effective and novel applications of machine learning, metaheuristic algorithms and deep learning. Many of these applications of AI to software development can be categorized as:
- Automation of software development activities including the creation of software artifacts (e.g., software test generation)
- Recommendation systems to assist software developers improve their performance (e.g., recommended code for review)
Not all Software Engineering research problems can be suitably addressed by AI techniques. A good first step to determine if a given software development problem can be addressed with AI is to see if it can be re-framed in terms of optimization, classification, prediction, etc. That is, can it be re-framed in terms of the type of problems that AI methods are effective at solving?
To find out more about the Software Quality Research Lab‘s work in this area please see the abstract and slides from my talk below. Continue reading
One of the questions I often get asked by new research students in my lab is how can they find research papers that are relevant to their thesis. For a student new to research this can be a very daunting task and doing a straight Google, Bing or Yahoo search generates a lot of noise (i.e. irrelevant content, non peer-reviewed papers, etc.).
The first advice I usually give is where to start searching. There are a number of academic-specific search engines that provide good results from a wide variety of researcher, publisher and academic websites. For example: Continue reading