Abstract
We studylazy structure sharing as a tool for optimizing equivalence testing on complex data types. We investigate a number of strategies for implementing lazy structure sharing and provide upper and lower bounds on their performance (how quickly they effect ideal configurations of our data structure). In most cases when the strategies are applied to a restricted case of the problem, the bounds provide nontrivial improvements over the naïve linear-time equivalence-testing strategy that employs no optimization. Only one strategy, however, which employs path compression, seems promising for the most general case of the problem.
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Work completed while at Princeton University and supported by a Fannie and John Hertz Foundation Fellowship, National Science Foundation Grant No. CCR-8920505, and the Center for Discrete Mathematics and Theoretical Computer Science (DIMACS) under NSF-STC-91-19999.
Work completed while at Princeton University and DIMACS and supported by DIMACS under NSF-STC-91-19999.
Research at Princeton University partially supported by the National Science Foundation, Grant No. CCR-8920505, the Office of Naval Research, Contract No. N00014-91-J-1463, and by DIMACS under NSF-STC-91-19999.
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Buchsbaum, A.L., Sundar, R. & Tarjan, R.E. Lazy structure sharing for query optimization. Acta Informatica 32, 255–270 (1995). https://doi.org/10.1007/BF01178261
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DOI: https://doi.org/10.1007/BF01178261