Fixed point theorems in generalized metric spaces with applications to computer science

Abstract

In 1994, Matthews introduced the notion of a partial metric space in order to obtain a suitable mathematical tool for program verification (Matthews in Ann. N.Y. Acad. Sci. 728:183-197, 1994). He gave an application of this new structure to formulate a suitable test for lazy data flow deadlock in Kahn's model of parallel computation by means of a partial metric version of the celebrated Banach fixed point theorem (Matthews in Theor. Comput. Sci. 151:195-205, 1995). In this paper, motivated by the utility of partial metrics in computer science, we discuss whether they are a suitable tool for asymptotic complexity analysis of algorithms. Concretely, we show that the Matthews fixed point theorem does not constitute, in principle, an appropriate implement for the aforementioned purpose. Inspired by the preceding fact, we prove two fixed point theorems which provide the mathematical basis for a new technique to carry out asymptotic complexity analysis of algorithms via partial metrics. Furthermore, in order to illustrate and to validate the developed theory, we apply our results to analyze the asymptotic complexity of two celebrated recursive algorithms. © 2013 Alghamdi et al.; licensee Springer.