Editing Breadth-first search (section)

== Applications ==
Breadth-first search can be used to solve many problems in graph theory, for example:
* Copying [[Garbage collection (computer science)|garbage collection]], [[Cheney's algorithm]]
* Finding the [[shortest path]] between two nodes ''u'' and ''v'', with path length measured by number of edges (an advantage over [[depth-first search]])<ref>{{cite book | title = Algorithms for Interviews | page = 144 | chapter = 4. Algorithms on Graphs | last1 = Aziz | first1 = Adnan | last2 = Prakash | first2 = Amit | date = 2010 | publisher = Algorithmsforinterviews.com | isbn = 978-1453792995 }}</ref>
* [[Cuthill–McKee algorithm|(Reverse) Cuthill–McKee]] mesh numbering
* [[Ford–Fulkerson algorithm|Ford–Fulkerson method]] for computing the [[maximum flow problem|maximum flow]] in a [[flow network]]
* Serialization/Deserialization of a binary tree vs serialization in sorted order, allows the tree to be re-constructed in an efficient manner.
* Construction of the ''failure function'' of the [[Aho-Corasick]] pattern matcher.
*Testing [[Bipartite graph#Testing bipartiteness|bipartiteness of a graph]].
*Implementing parallel algorithms for computing a graph's transitive closure. <ref>{{cite book |last1=Dhulipala |first1=Laxman |last2=Blelloch |first2=Guy E. |last3=Shun |first3=Julian |title=Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable |date=August 21, 2019 |page=17 |doi=10.1145/3210377.3210414 |arxiv=1805.05208 |isbn=9781450357999 |s2cid=44126609 }}</ref>