"We have it all wrong" ...so what are you doing to change practice?

Along with many other researchers, I share the view that a systematically coherent research program, in both theory and applications of algorithms, is definitely needed to accelerate innovation in computing. We routinely design computational approaches and engage in healthy competitions where the performance of our methods is tested... but what if "We have it all wrong"? What if we need a paradigmatic change in our practice for the development and design of computational methods? We may need to enrich our practice with a new approach.

In fact, John N. Hooker already alerted the computing and mathematical community more than 20 years ago Hooker1995: "Competitive testing tells us which algorithm is faster but not why." Hooker argued for a more scientific approach and he proposed the use of "controlled experimentation". This is common in empirical sciences. "Based on one's insights into an algorithm", he said, "one may expect good performance to depend on a certain problem characteristic". Then "design a controlled experiment that checks how the presence or absence of this characteristic affects performance" and, finally, "build an exploratory mathematical model that captures the insight [...] and deduce from its precise consequences that can be put to the test".

In this talk, I will address how a new thinking is needed for the development of our field. I will have an with emphasis in our success on both speeding up solutions for the traveling salesman problem as well as our success to create very hard instances for the world's fastest solver.