Abstract
A new dynamic Interpolation Search (IS) data structure is presented that achieves O(loglogn) search time with high probability on unknown continuous or even discrete input distributions with measurable probability of key collisions, including power law and Binomial distributions. No such previous result holds for IS when the probability of key collisions is measurable. Moreover, our data structure exhibits O(1) expected search time with high probability for a wide class of input distributions that contains all those for which o(loglogn) expected search time was previously known.
This work was partially supported by the FET Unit of EC (IST priority – 6th FP), under contracts no. IST-2002-001907 (integrated project DELIS) and no. FP6-021235-2 (project ARRIVAL), and by the Action PYTHAGORAS with matching funds from the European Social Fund and the Greek Ministry of Education.
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Kaporis, A., Makris, C., Sioutas, S., Tsakalidis, A., Tsichlas, K., Zaroliagis, C. (2006). Dynamic Interpolation Search Revisited. In: Bugliesi, M., Preneel, B., Sassone, V., Wegener, I. (eds) Automata, Languages and Programming. ICALP 2006. Lecture Notes in Computer Science, vol 4051. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11786986_34
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DOI: https://doi.org/10.1007/11786986_34
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