What We Know We Don't Know: Introduction to Empirical Software Engineering
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There are many things in software we believe are true but very little we know. Maybe testing reduces bugs, or maybe it's just superstition. If we want to improve our craft, we need a way to distinguish fact from fallacy. We need to look for evidence, placing our trust in hard data.
Empirical Software Engineering is the study of what actually works in programming. Instead of trusting our instincts we collect data, run studies, and peer-review our results. This talk is all about how we empirically find the facts in software and some of the challenges we face, with a particular focus on software defects and productivity.
Who should attend this talk: People interested in improving their practices. People interested in how we determine "best practices". Architects and managers who want to know the processes that produce the best software.
Academic level: Beginner for academics. Intermediate for industry.
What is the take away in this talk: Why we need to empirically evaluate claims. How we do it. What we know, with hard evidence, improves our software. How to explore the research yourself.
