The Role of Science and Mathematics in Software Development
50:56
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2 years ago
This talk addresses the growing realization that a return to the scientific method is an essential ingredient for future success in algorithm design and in software development.
To set the stage, a brief introduction will focus on the unfortunate fact that science and mathematics are strangely absent from typical introductory computer science (CS) courses. Recent efforts have shown that one effective way to address the situation is to introduce CS to science/engineering students and science/engineering to CS students in the same course.
The talk is centered on a detailed illustrative example involving the behavior of algorithms for finding a path from a source to a destination in a graph, an operation that is critical in a broad variety of applications, from statistical physics to combinatorial optimization to image processing. The basic performance characteristics of the numerous known algorithms for solving this problem (which are elementary) are actually poorly understood. Developing such understanding will lead to the discovery of new approaches that are dramatically more effective than those in common use. This example illustrates that software developers and algorithm designers who depend upon untested theories instead of scientific studies to evaluate algorithms are taking risks and missing opportunities.
Concluding remarks will describe research directions in the field of analytic combinatorics, which provides the mathematical foundations in support of such studies.This talk addresses the growing realization that a return to the scientific method is an essential ingredient for future success in algorith...all »This talk addresses the growing realization that a return to the scientific method is an essential ingredient for future success in algorithm design and in software development.
To set the stage, a brief introduction will focus on the unfortunate fact that science and mathematics are strangely absent from typical introductory computer science (CS) courses. Recent efforts have shown that one effective way to address the situation is to introduce CS to science/engineering students and science/engineering to CS students in the same course.
The talk is centered on a detailed illustrative example involving the behavior of algorithms for finding a path from a source to a destination in a graph, an operation that is critical in a broad variety of applications, from statistical physics to combinatorial optimization to image processing. The basic performance characteristics of the numerous known algorithms for solving this problem (which are elementary) are actually poorly understood. Developing such understanding will lead to the discovery of new approaches that are dramatically more effective than those in common use. This example illustrates that software developers and algorithm designers who depend upon untested theories instead of scientific studies to evaluate algorithms are taking risks and missing opportunities.
Concluding remarks will describe research directions in the field of analytic combinatorics, which provides the mathematical foundations in support of such studies.«
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