Data Structures and Algorithms (Software Engineering and by Shi-Kuo Chang

By Shi-Kuo Chang

This can be a good, up to date and easy-to-use textual content on facts constructions and algorithms that's meant for undergraduates in laptop technology and knowledge technology. The 13 chapters, written by means of a global workforce of skilled lecturers, conceal the basic strategies of algorithms and many of the very important info constructions in addition to the idea that of interface layout. The publication comprises many examples and diagrams. every time acceptable, application codes are incorporated to facilitate studying.

This e-book is supported by means of a global workforce of authors who're specialists on facts buildings and algorithms, via its site, so that either academics and scholars can make the most of their services.

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6. Analysis of the Execution Time of a Program In this paragraph, we introduce the analysis of the execution time of a program. We begin by analyzing the execution time of simple instructions, then we deal with the control instructions and finally we show a method­ ology for the computation of the execution time of a program. 1. , have a constant execution time equal to 0(1). e. ) The same consideration is valid for instructions such as cin (cout) that copy a number of data from the input file to the output file.

C o m p a r i s o n s B e t w e e n Different E x e c u t i o n T i m e s One aspect for the measure of a quantity is the identification of a "weight" of the component entity. This is obtained by first defining a measure and then a methodology to compute the measure. In our specific case we have defined a temporal measure in a conventional manner and we are going to describe a methodology for measuring the performance of a program. However, one of the problems to consider is the comparison between the execution time of programs of different complexity, when executed on the same computer.

In that case the upper limit of the time execution is the max execution time between the two. (c) If (condition) {} else {} • Condition -> 0(1) • "else" branch —> the upper limit of the execution time is g{n)• "then" branch —> the upper limit of the execution time is 0(g(n)) because f(n) is 0(g(n)) If /(n) and g(n) 0(max(/(n),g(n))) are not Big-0 of each other then O(if) = The Running Time of an Algorithm 29 Example if A[l][l] = 0 for (i = 1; i < n; i++) for (j = 1; j < n; i++) A[i][j] = 10; else for (i = 1; i < n; i++) 0(max(n 2 ,n)) = 0 ( n 2 ) Fig.

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