数据结构的C++伪码实现(英文版) pdf epub mobi txt 电子书 下载 2026

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出版者:人民邮电出版社

作者:Richard F.Gilberg

出品人:

页数:684

译者:

出版时间:2002-1-1

价格:55.00

装帧:平装(无盘)

isbn号码:9787115097668

丛书系列:国外著名高等院校信息科学与技术优秀教材（英文版）

图书标签:

• 数据结构
• programming
• C++
• 计算机
• 算法
• C
• Data Structures
• C++
• Pseudocode
• Algorithms
• Computer Science
• Programming
• Implementation
• Educational
• Textbook
• Reference
• STEM

A detailed and comprehensive guide in C++ style presents data structures as practical tools for organizing, managing, and accessing information efficiently. This book explores fundamental constructs from scratch, emphasizing implementation clarity, algorithmic efficiency, and real-world applicability. Starting with arrays, the text delves into static linear collections that store homogeneous elements in contiguous memory—offering direct access via index but limited flexibility. Pointers are introduced early not as magic tools but as essential mechanisms for dynamic control over memory allocation and structure modification. Linked structures follow naturally: singly and doubly linked lists provide dynamic size capabilities, enabling insertions and deletions at arbitrary positions without costly shifts, though at the cost of sequential access. The book develops these with iterators and node classes that encapsulate both data and links, revealing how abstraction supports maintainability and reuse. Structs and simple classes form the foundation of object-oriented data modeling. Rather than abstracting away implementation, readers learn to craft custom types that bundle values with meaningful semantics—critical for domain-specific clarity. Operator overloading is introduced not as a syntactic trick but as a means to make code expressive and intuitive, bridging high-level intent with low-level execution. Trees emerge as hierarchical models central to sorting, searching, and divide-and-conquer strategies. Binary search trees enforce ordered relationships, allowing logarithmic time complexity for insertion and lookup under balanced conditions. Balanced variants like AVL or Red-Black trees automatically maintain structure, ensuring performance guarantees. The text presents tree operations—traversals, splits, merges—with emphasis on invariants that sustain correctness across modifications. Hashing is explored as a cornerstone of fast data retrieval. Through open addressing and chaining, readers implement collision resolution techniques while analyzing load factors and rehashing costs. Performance trade-offs between memory usage and access speed are discussed in depth, illustrating how hash tables underpin dictionaries, caches, and index structures across software systems. Advanced topics include graphs—modeled via adjacency lists or matrices—and their traversal algorithms: depth-first search reveals connectivity and pathfinding potential, while breadth-first search excels in shortest-path calculations on unweighted networks. Heaps are presented as efficient priority queues, supporting dynamic order maintenance with logarithmic insertions and extractions—vital for scheduling and simulation systems. Memory management is treated rigorously: manual control via raw pointers is balanced with smart pointers and RAII principles to prevent leaks, aligning with modern C++ best practices. Templates enable generic data structures that adapt across types without sacrificing performance or safety. Extemplates and move semantics further refine efficiency by minimizing unnecessary copies during construction and destruction. Each chapter builds on prior concepts through carefully designed exercises embedded directly in code, reinforcing theory with hands-on implementation. Algorithms for sorting—quicksort’s partition logic, merge sort’s recursive divide-and-conquer, and heapsort’s priority-based extraction—are presented not as isolated routines but as interwoven components of a broader computational strategy. The narrative stresses correctness through invariants: loop conditions, pointer stability, and resource ownership are scrutinized to prevent subtle bugs that undermine reliability. Performance analysis includes Big-O notation applied in context, helping readers predict scalability across data volumes. Throughout, examples use familiar data—integers, strings, pointers—to ground abstract ideas, while progressive complexity introduces concurrency basics: mutexes for thread-safe access, atomic operations where needed—preparing learners for real-world parallel systems. By focusing on implementation detail and practical utility rather than theory alone, this book serves as both a reference and a companion for engineers seeking to master data structures in C++. It bridges academic rigor with engineering pragmatism, ensuring that readers emerge not just with knowledge, but with the craftsmanship to build robust, efficient software systems from structured data foundations.

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我不得不承认，这本书的英文原版在学术界的声誉一直是颇高的，但这并不意味着它就高不可攀。我是在准备一个重要的技术面试时开始研读它的，当时我的核心诉求是快速而准确地掌握那些核心算法的精髓。这本书的独特之处在于它对“伪代码”的坚持和打磨。不同于直接堆砌特定语言的语法，作者提供的伪代码仿佛是算法思想的纯粹载体，它屏蔽了C++语言特有的那些繁琐的句法细节，使得读者可以将全部注意力集中在数据流转和逻辑判断之上。举例来说，在描述堆排序（Heap Sort）的维护过程时，书中提供的伪代码片段简洁到令人拍案叫绝，每一个变量的声明和循环条件的设置都充满了数学美感，读起来如同在欣赏一段精妙的数学证明。这种对底层逻辑的纯粹呈现，极大地增强了我对递归、迭代等编程范式的理解深度，远超我之前阅读过的任何一本侧重于特定语言实现的参考书。

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这本书的排版和视觉呈现，初看之下可能会让人觉得有些传统，甚至略显刻板，但随着阅读的深入，我开始体会到这种“刻板”背后的深思熟虑。在诸如平衡二叉树（AVL Tree或Red-Black Tree）这种结构复杂的章节中，作者通过大量的ASCII艺术图和结构示意图，将节点的旋转、颜色的翻转等动态过程静态地固定在了纸面上。这些图示不是简单的装饰，而是解读复杂操作流程的关键钥匙。我注意到，对于每一个重要的算法步骤，作者都配有对应的小段文字注释，这些注释往往一针见血地指出了该步骤的目的和可能存在的陷阱。这使得即便是像B树（B-Tree）这种涉及多级索引管理的复杂结构，在我脑海中也能构建出一个清晰的三维模型。这种注重细节、极度严谨的编排方式，极大地降低了认知负荷，让读者能够更专注于算法的逻辑内核而非图表的解读。

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这本书的整体阅读体验非常流畅，这要归功于其对英文术语使用的恰当把控。作者在引入新的数据结构或算法时，总是先用清晰、规范的术语进行定义，然后才展开具体的描述。这对于希望巩固或提升自身技术英文词汇的读者来说，无疑是一个巨大的加分项。我发现，当我在查阅其他技术文档或阅读前沿论文时，许多曾经模糊的术语——比如“amortized analysis”（摊还分析）——在这本书中得到了最清晰的阐释。书中的例子选择也极具代表性，它们往往是教科书级别难题的最精炼版本，既能展示算法的强大能力，又不会因为过于复杂的输入数据而分散读者的注意力。总而言之，这本书不仅是一本学习数据结构的教材，更是一本提升技术阅读和思维规范化的优秀工具书。

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对于一位有着多年编程经验的开发者而言，我们需要的往往不是最基础的入门指导，而是对高级概念的精深剖析。这本书恰恰在这方面展现了其卓越的价值。它并没有将篇幅过多地浪费在对“什么是数组”这类基础概念的重复讲解上，而是迅速切入到更具挑战性的领域，例如高级图算法中的最短路径变种，或者动态规划（Dynamic Programming）的自底向上与自顶向下实现的对比分析。特别是关于内存管理与数据结构结合的部分，虽然只是寥寥数页，但其对缓存一致性、局部性原理在链表和数组访问中的体现的讨论，展现了作者深厚的系统级理解。这种对性能优化背后理论支撑的挖掘，让我对以往依赖库函数实现的功能有了更深一层的敬畏和理解，它不再仅仅是“能跑起来的代码”，而是“经过深思熟虑的计算模型”。

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这本厚重的书册，初拿到手时，便被它那份沉甸甸的质感所吸引。装帧设计走的是一种低调的实用主义路线，没有太多花哨的图形，封面上的字体排列也显得十分规整。我翻开扉页，首先映入眼帘的是那份详尽的目录，它像一张精确绘制的地图，将整本书的脉络清晰地勾勒出来。从基础的线性结构，到复杂的图论算法，每一步的推进都显得逻辑严密。我尤其欣赏作者在章节安排上的匠心独运，他似乎深谙初学者在面对抽象概念时的困惑，总能巧妙地将理论知识与实际的编程逻辑点滴渗透，让人在阅读过程中有一种水到渠成的豁然开朗感。书中对各种数据结构的操作复杂度分析部分，更是做到了深入浅出，即便是对于那些以“时间复杂度”为畏途的读者，也能通过那些详尽的数学推导和直观的图示，迅速建立起对性能瓶颈的直观认知。总而言之，它给人的感觉不是一本冰冷的教科书，而更像是一位经验丰富、耐心十足的导师，手把手地引导你穿越数据结构的迷雾森林。

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