D. Merlini
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引用次数: 0

摘要

使用Knuth在他的《计算机程序设计艺术》系列书中推广的方法,以及后来由Sedgewick和Flajolet在《算法分析入门》一书中推广的方法,向计算机科学学位的学生教授算法分析并不是一项简单的任务,因为一般来说,这些学生对算法的实现比相应的理论方面更感兴趣。该方法通过使用基于递归关系和生成函数等符号工具的方法,确定算法的最佳、最差和平均情况性能,从而精确地表征算法的性能。最困难的方面是理解平均情况,因为这对应于在可能的输入变化时研究算法:这代表了最重要的目标,因为通常学生在理解对应于特定输入配置的最佳和最差情况方面没有困难。多年来,一种成功的折衷方法是,先教学生分析问题,然后用符号计算系统对算法进行模拟,以便精确地检查理论结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of algorithms as a teaching experience
Teaching analysis of algorithms to students in Computer Science degrees, using the approach popularized by Knuth in his series of books ``The Art of Computer Programming" and later by Sedgewick and Flajolet in the book ``An Introduction to the Analysis of Algorithms", is not a simple task since, in general, these students are more interested in the implementation of an algorithm than in the corresponding theoretical aspects. This approach concentrates on precisely characterizing the performance of algorithms by determining their best, worst and average case performance using a methodology based on symbolic tools such as recurrence relations and generating functions.The most difficult aspect is to understand the average case since this corresponds to studying the algorithm as its possible inputs vary: this represents the most important goal since generally students have no difficulty in understanding the best and worst cases, corresponding to particular input configurations.A compromise that has been successful over the years consists in teaching students the analytical aspects of the problem and then organize a simulation of the algorithm with a system of symbolic computation in order to precisely check the theoretical results.
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