Results 1 
4 of
4
Modeling the Storage Architectures of Commercial Database Systems
 ACM Transactions on Database Systems
, 1985
"... Modeling the storage structures of a DBMS is a prerequisite to understanding and optimizing database performance. Previously, such modeling was very difficult because the fundamental role of conceptualtointernal mappings in DBMS implementations went unrecognized. In this paper we present a model o ..."
Abstract

Cited by 19 (5 self)
 Add to MetaCart
(Show Context)
Modeling the storage structures of a DBMS is a prerequisite to understanding and optimizing database performance. Previously, such modeling was very difficult because the fundamental role of conceptualtointernal mappings in DBMS implementations went unrecognized. In this paper we present a model of physical databases, called the transformation model, that makes conceptualtointernal mappings explicit. By exposing such mappings, we show that it is possible to model the storage architectures (i.e., the storage structures and mappings) of many commercial DBMSs in a precise, systematic, and comprehendible way. Models of the INQUIRE, ADABAS, and SYSTEM 2000 storage architectures are presented as examples of the model’s utility. We believe the transformation model helps bridge the gap between physical database theory and practice. It also reveals the possibility of a technology to automate the development of physical database software.
Fringe Analysis Revisited
"... Fringe analysis is a technique used to study the average behavior of search trees. In this paper we survey the main results regarding this technique, and we improve a previous asymptotic theorem. At the same time we present new developments and applications of the theory which allow improvements in ..."
Abstract

Cited by 12 (5 self)
 Add to MetaCart
Fringe analysis is a technique used to study the average behavior of search trees. In this paper we survey the main results regarding this technique, and we improve a previous asymptotic theorem. At the same time we present new developments and applications of the theory which allow improvements in several bounds on the behavior of search trees. Our examples cover binary search trees, AVL trees, 23 trees, and Btrees. Categories and Subject Descriptors: F.2.2 [Analysis of Algorithms and Problem Complexity ]: Nonnumerical Algorithms and Problems  computations on discrete structures; sorting and searching; E.1 [Data Structures]; trees. Contents 1 Introduction 2 2 The Theory of Fringe Analysis 4 3 Weakly Closed Collections 9 4 Including the Level Information 11 5 Fringe Analysis, Markov Chains, and Urn Processes 13 This work was partially funded by Research Grant FONDECYT 930765. email: rbaeza@dcc.uchile.cl 1 Introduction Search trees are one of the most used data structures t...
§1. Keyed Search Structures Lecture III Page 1 Lecture III BALANCED SEARCH TREES
"... Anthropologists inform that there is an unusually large number of Eskimo words for snow. The Computer Science equivalent of snow is the tree word: we have (a, b)tree, AVL tree, Btree, binary search tree, BSP tree, conjugation tree, dynamic weighted tree, finger tree, halfbalanced ..."
Abstract
 Add to MetaCart
(Show Context)
Anthropologists inform that there is an unusually large number of Eskimo words for snow. The Computer Science equivalent of snow is the tree word: we have (a, b)tree, AVL tree, Btree, binary search tree, BSP tree, conjugation tree, dynamic weighted tree, finger tree, halfbalanced