Implementing Algorithms

 Estonian Winter School in Computer Science, February - March 2005


 

Algorithms are problem solving recipes intended for humans; they are usually expressed in a mixture of natural language, mathematical notation, and programming notation. In contrast, programs are intended for machine execution; they are expressed in a programming language.

How do we go from a correct algorithm to a correct program?

The background for my lectures is the experience with LEDA, CGAL, and EXACUS, three algorithm library projects I was involved with.

In the first main part, I discuss certifying algorithms. Certifying algorithms return not only the value they are supposed to compute but also a witness (certificate) which allows the user of the algorithm to convince itself of the correctness of the value returned. I give examples of certifying algorithms and discuss the limits of certification.

In the second main part, I discuss the implementation of geometric algorithms. Their implementation is particularly difficult, because geometric algorithms are usually designed for inputs in general position and for the Real-RAM model of computation. I give examples, how miserably naive implementations can fail, show how to realize a Real-RAM as needed for computational geometry, discuss approaches to overcome the general position problem, and finally come to exact algorithms for curves and surfaces.

I recommend that you read through the slides of the talk on LEDA. 
On an input x, a certifying algorithm for a function f does not only return y, the alleged function value f(x), but also a certificate (proof, convincing evidence) of the equality ``y = f(x)''. In this way, a user of the program can convince himself that the program worked correctly on the given input x. We advocate certifying programs as a pragmatic approach to program correctness.


Prof. Dr. Kurt Mehlhorn
Max-Planck-Institut für Informatik
Algorithms and Complexity Group (AG1)
Im Stadtwald
66123 Saarbrücken
Germany