Kenneth Oksanen

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Balanced binary search trees are widely used main memory index structures. They provide for logarithmic cost for searching, insertion, deletion, and eecient ordered scanning of keys. Long term trends in computer technology have emphasized the eeect of memory reference locality on algorithm performance. For example, the search performance of large(More)
Detecting a given algorithm in a program without access to its source code can be valuable in many tasks ranging from intellectual property management to verifying the program's security properties. Unfortunately, approaches based on decompiling or reverse-engineering the program suffer from prohibitive costlyness as well as theoretical limitations. Instead(More)
Memory reference locality is widely known to have an increasingly important eeect on the performance of algorithms. We demonstrate and explain why the performance of the binary tree search algorithm varies considerably depending on how the tree is laid out in the main memory. We present an algorithm which relocates a binary tree so that maximal performance(More)
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