A Tradeoff Between Search and Update Time for the Implicit Dictionary Problem

This paper proves a tradeoff between the time it takes to search for elements in an implicit dictionary and the time it takes to update the value of elements in specified locations of the dictionary. It essentially shows that if the update time is constant, then the search time is ω(nɛ) for some constant ɛ>0.

[1]  Allan Borodin,et al.  Efficient Searching Using Partial Ordering , 1981, Inf. Process. Lett..

[2]  Harry G. Mairson Average case lower bounds on the construction and searching of partial orders , 1985, 26th Annual Symposium on Foundations of Computer Science (sfcs 1985).

[3]  J. Ian Munro An Implicit Data Structure for the Dictionary Problem that Runs in Polylog Time , 1984, FOCS.

[4]  J. IAN MUNRO,et al.  An Implicit Data Structure Supporting Insertion, Deletion, and Search in O(log² n) Time , 1986, J. Comput. Syst. Sci..

[5]  J. Ian Munro,et al.  Implicit Data Structures for Fast Search and Update , 1980, J. Comput. Syst. Sci..

[6]  Greg N. Frederickson,et al.  Implicit Data Structures for the Dictionary Problem , 1983, JACM.

[7]  Kurt Mehlhorn,et al.  Partial Match Retrieval in Implicit Data Structures , 1981, Inf. Process. Lett..

[8]  Andrew Chi-Chih Yao,et al.  Should tables be sorted? , 1981, 19th Annual Symposium on Foundations of Computer Science (sfcs 1978).

[9]  Kurt Mehlhorn,et al.  Searching Semisorted Tables , 1985, SIAM J. Comput..

[10]  Michael E. Saks,et al.  Information bounds are good for search problems on ordered data structures , 1983, 24th Annual Symposium on Foundations of Computer Science (sfcs 1983).