Continuing the recent trend, in this article we design several space-efficient algorithms for two well-known graph search methods. Both these search methods share the same name breadth-depth search (henceforth BDS), although they work entirely in different fashion. The classical implementation for these graph search methods takes O(m+n) time and (formula presented) bits of space in the standard word RAM model (with word size being (formula presented) bits), where m and n denotes the number of edges and vertices of the input graph respectively. Our goal here is to beat the space bound of the classical implementations, and design (formula presented) space algorithms for these search methods by paying little to no penalty in the running time. Note that our space bounds (i.e., with (formula presented) bits of space) do not even allow us to explicitly store the required information to implement the classical algorithms, yet our algorithms visits and reports all the vertices of the input graph in correct order.
CITATION STYLE
Chakraborty, S., Mukherjee, A., & Satti, S. R. (2019). Space Efficient Algorithms for Breadth-Depth Search. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11651 LNCS, pp. 201–212). Springer Verlag. https://doi.org/10.1007/978-3-030-25027-0_14
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