Download Efficient Data Management in E-Business Transactions by Nikos Karacapilidis PDF

By Nikos Karacapilidis

Show description

Read Online or Download Efficient Data Management in E-Business Transactions PDF

Best algorithms and data structures books

Algorithmic Foundation of Multi-Scale Spatial Representation (2006)(en)(280s)

With the common use of GIS, multi-scale illustration has turn into an immense factor within the realm of spatial information dealing with. targeting geometric modifications, this source provides complete assurance of the low-level algorithms to be had for the multi-scale representations of alternative different types of spatial positive factors, together with element clusters, person traces, a category of traces, person components, and a category of parts.

INFORMATION RANDOMNESS & INCOMPLETENESS Papers on Algorithmic Information Theory

"One will locate [Information, Randomness and Incompleteness] every kind of articles that are popularizations or epistemological reflections and displays which allow one to speedily receive an actual suggestion of the topic and of a few of its functions (in specific within the organic domain). Very whole, it is suggested to someone who's attracted to algorithmic details conception.

A Method of Programming

Booklet via Dijkstra, Edsger W. , Feijen, W. H. J. , Sterringa, comic story

Extra resources for Efficient Data Management in E-Business Transactions

Sample text

2 Complexity Theory 32 Therefore, no direct recursive calls are needed. As a consequence, the performance increases drastically. The divide-and-conquer algorithm for the Fibonachi-numbers reads as follows, the array f [Iis used t o store the results: algorithm fib-dynamic(n) begin i f n < 3 then return 1; f[l]:= 1; f [a] := 1; for i := 3 , 4 , . . , n do f [i] := f [i- 1 1 f [i - 21 returnf [n]; end + Since the algorithm contains just one loop it runs in O(n) time. The last basic programming principle which is presented here is backtracking.

Since the tree is not empty and 24 is smaller than the object at the root (33), a recursive call with the left subtree occurs. Here, number 17 is stored at the root. Thus, the procedure is called with the right subtree of the first subtree. In the next step again the search continues in the right subtree where finally the object is found. The algorithm performs one descent into the tree. Hence, its time complexity is O(h) if h is the height of the search tree. If the search tree is complete, the height is h E O(logn), where n is the number of elements in the tree.

N/2 do comment divide set begin B 2. - A 2 ,. C z. - A z+n/2; end mergesort(n/2, {Bl, . . ,Bn12)); comment sort subsets mergesort(n/2, {GI,. . , CnI2)); x := 1;y := I ; comment largest elements of sequences for i := 1,.. ,n do comment merge sorted subsets if x 5 n/2 AND B, < C, then Ai := B,; x := x 1; else A 2. - cy ,. y := y I ; end '- + + The hierarchy of recursive calls of mergesort(4, {5,2,3,1)) is displayed in the upper part of Fig. 10. In the lower part the merging of the sorted subset is shown.

Download PDF sample

Rated 4.77 of 5 – based on 46 votes
 

Author: admin