A new approach to speed up combinatorial search strategies using stack and hash table

Abstract

Owing to the significance of combinatorial search strategies both for academia and industry, the introduction of new techniques is a fast growing research field these days. These strategies have really taken different forms ranging from simple to complex strategies in order to solve all forms of combinatorial problems. Nonetheless, despite the kind of problem these approaches solve, they are prone to heavy computation with the number of combinations and growing search space dimensions. This paper presents a new approach to speed up the generation and search processes using a combination of stack and hash table data structures. This approach could be put to practice for the combinatorial approaches to speed up the generation of combinations and search process in the search space. Furthermore, this new approach proved its performance in diverse stages better than other known strategies.

Fuzzy adaptive tuning of a particle swarm optimization algorithm for variable-strength combinatorial test suite generation

“…However, these were not efficient when the number of input parameters grows due to the long generation time. More recently, we have developed an efficient algorithms algorithm using a new stack and hash table data structure [49]. Here should be noted that the same algorithm could be used for the VS-CIT.…”