Data Structures, Fall 2007

最新推荐文章于 2024-09-28 13:00:16 发布
最新推荐文章于 2024-09-28 13:00:16 发布 · 3.9k 阅读 · 0

Data Structures, Fall 2007

���Ƶ��c

Course Information
InstructorIris Hui-Ru Jiang (hrjiang@faculty.nctu.edu.tw) ext. 31211, ED540
Lecture TimeMondays B, Thursdays EF@EC016
(from Oct. 1st, 2007)
Text

Text: E. Horowitz, S. Sahni, and D. P. Mehta, Fundamentals of Data Structures in C++, 2nd Ed., Silicon Press, 2007. ISBN: 0929306376.

Reference 1H. Deitel and P. Deitel, C++ How to Program, 5th Ed., Prentice Hall, 2005. ISBN: 0131971093.
Reference 2T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to
Algorithms, 2nd Ed., MIT Press/McGraw Hill, 2001. ISBN: 0-262-03293-7/0-07-
013151-1.
Reference 3J. Kleinberg and E. Tardos, Algorithm Design, Pearson, 2006. ISBN: 0-321-
37291-3.
TAWan-Yu Lee and Liang-Gi Chang (ds.2007fall@gmail.com) ext. 54236, ED518
Grading InformationFinal status: grading (2008/02/02)

1. Final grading (2008/02/02)
2. Happy Chinese New Year!
3.

Syllabussyllabus (2007/09/10)
Administrative Matterslec0 (2007/09/18)
Article�ڤ����D-���a�P (2007/07/30 �p��) (2007/09/18)
ArticleWhy universities require CS students to take math? (2007/09/18)

Address

Steve Jobs' commencement address at Stanford, June 2005 (2008/01/03)

Chapter 1lec1 (2007/09/19, pp. 16-25 slightly modified, pp. 26-40 added)
Chapter 2lec2 (2007/10/05, pp. 17, 18, 23, 24 updated)
Chapter 3lec3 (2007/10/24, pp. 29-37 added)
Chapter 4lec4 (2007/11/04, pp. 39~ added)
Chapter 5lec5 (2008/01/14, pp. 27, 30, 58 updaed)
Chapter 6 lec6 (2008/01/14, pp. 23, 36 updated)
Chapter 7lec7 (2007/12/28, pp. 12, 13, 20, 21 updated)
Chapter 8 lec8 (2008/01/01, pp. 8 updated)

Homework 1

hw1 (2007/09/20) readme (2007/09/27) ex1 (2007/09/28) solution (2007/11/05)

Homework 2

hw2 (2007/10/05) readme (2007/10/18) solution (2007/11/05)

Homework 3

hw3 (2007/10/25) readme (2007/10/29) solution (2007/11/12)

Program 2

prog2 (2007/11/05, updated in BLUE) due 11:59pm, Nov. 11. Late submission open! (2007/11/15)

Homework 4

hw4 (2007/11/05) solution (2007/11/12, 10% bonus)

Program 3

prog3 (2007/11/23) test cases (2007/12/01) readme (2007/12/06)

Homework 5

hw5 (2007/12/14) solution (2008/01/08)

Program 4

prog4 (2008/01/01, modification is highlighted in red) test cases (2007/12/21) example (2008/01/03, pp. 4 updated) demo (2008/01/07)

Homework 6

hw6 (2007/12/28) solution (2008/01/08)

1. MIT's OpenCourseWare - free online course materials for self learners.
2. Algorithms - Prof. Y.-W. Chang, NTU GIEE, Fall 2006
3. Communications of the ACM
4. IEEE Spectrum
5. STL consists of numerous implementations for data structures, graph algorithms, etc.
6. LEDA also consists of numerous implementations for data structures, graph algorithms, etc.
7. Microsoft Developer Network has nice documents.
8. Source codes for the textbook.
9. Microsoft Developer Network has nice documents.
10.
iteye_8601
关注
数据结构 in c++（中文版）Fundamentals_of_Data_Structures_in_C++_by_Horowitz
09-30
Fundamentals_of_Data_Structures_in_C++_by_Horowitz_1997 最经典的数据结构教材的中文版（很多学校用的都是英文影印版吧）
class notes for DataStructures
09-18
These lecture notes grew out of class notes provided for the students in CSCI 104 (“Data Structures and Object-Oriented Design”) at the University of Southern California in Fall of 2013.
数据结构基础(C++语言版)(第2版)
乐吾天
08-30 1958
数据结构基础(C++语言版)(第2版) 查看选用该教材的高校　 精彩评论 点击看大图市场价 ：￥49.00 普通会员 ： ￥41.65 1-3星会员： ￥40.67 4-5星会员： ￥39.20 校园优惠价 ：￥40.67(83折) (马上了解) 加入教材预订单 new   （50天教材预留服务）
《FUNDAMENTALS OF DATA STRUCTURES IN C 》课后习题答案
weixin_30314813的博客
11-17 1008
最近在当当上买了《FUNDAMENTALS OF DATA STRUCTURES IN C》，在上班之余看看，会不定时发布自己的课后习题解答！ 一定要坚持哦~~ 转载于:https://www.cnblogs.com/matrix1024/archive/2011/11/17/2252806.html...
CSC3100 Data Structures Fall 2024 Programming 1C/C++
bilimint的博客
09-28 876
3100DataStructuresFall2024Assignment0 0 0 1 -231 5 1 2 -131 3 2 1 1333410 10 531 2 4 4 -121 3 1 2 -13231 2 4 4 13-58-98TestCaseNo.1-45-78-10n,m≤20n,m≤5×103n,m≤10• Choose•6 4 45 5 217 36 4 4。
CS50 第五周 Data Structures
Anxonz的博客
11-04 218
三种可能的等位基因是 A、B 和 O，每个人都有两个（可能相同，也可能不同）。每个孩子的父母会随机地将自己的两个血型等位基因之一传递给他们的孩子。因此，可能的血型组合有：OO、OA、OB、AO、AA、AB、BO、BA 和 BB。例如，如果一个父亲的血型是AO，另一个父亲的血型是BB，那么孩子的可能血型将是AB和OB，具体取决于从每个父亲那里接收了哪个等位基因。同样，如果一个父亲的血型是AO，另一个父亲的血型是OB，那么孩子的可能血型将是AO、OB、AB 和 OO。
Go Data Structures: Interfaces
weixin_34307464的博客
01-15 129
refer:http://research.swtch.com/interfaces Go Data Structures: Interfaces Posted on Tuesday, December 1, 2009. Go's interfaces—static, checked at compile time, dynamic when asked for—are,...
COMP3506/7505 Algorithms and Data Structures
vx_codinghelp的博客
09-01 928
Summarystructureswarmupwarmup.pymalloclabs???on.???1.???6, 4, 9??????or?
CSC3100 Data Structures
sandwitch5的博客
11-27 877
InputOutput1231SolutionsJavaint a, b;} }PythonCint A, B;return 0;C++int A, B;return 0;2FAQsAuthors3|B|−1 |B|i=1 j =i+11.2 Input。
积分java源码-COMP251_Fall2020_Algorithms-and-Data-Structures:COMP251_Fall20
06-06
积分java源码COMP251 2020 秋季算法和数据结构 课程资料 本课程所需的所有材料都将在公共课程网页上提供。 没有必要的教科书。 但是，我们推荐以下教科书，大多数讲座将基于这些教科书： [CLRS2009] ...
Advanced_Data_Structures_Projects:高级数据结构项目
06-15
Advanced_Data_Structures_Projects 这是一个项目示例，重点介绍了我在课程 [EC 504 at Boston University Fall 2014.] ( ) 本课程涵盖了从算法分析到动态规划解决方案（如经典的 Dijkstra 和 Bellman-Ford）的...
285个地级市邻接矩阵、经济地理矩阵等8个矩阵数据（2003-2023年）
11-25
01、数据简介 共八个矩阵，各类矩阵通过量化空间关系，为区域政策制定（如交通规划、产业布局）和学术研究（如空间溢出效应、区域收敛）提供关键工具，需根据研究目标灵活选择或组合使用。 数据名称：285个地级市邻接矩阵、经济地理矩阵等8个矩阵数据 数据年份：2003-2023年 参考文献：邵帅,李欣,曹建华,杨莉莉.中国雾霾污染治理的经济政策选择——基于空间溢出效应的视角[J].经济研究,2016,51(09):73-88. 02、相关数据 地级市人均GDP、空间邻接矩阵、空间经济距离矩阵（GDP）、空间地理距离矩阵（经纬度）、空间地理距离倒数平方矩阵（经纬度）、经济地理权重矩阵（GDP和经纬度）、经济地理嵌套矩阵（GDP和经纬度）、空间经济矩阵（非对称）、空间经济地理矩阵（非对称）、纬度、经度、距离
【影视数据分析】基于C++的多维度可视化系统设计：实现高效实时数据处理与交互式决策支持 项目介绍 基于C++的影视数据可视化系统设计和实现的详细项目实例（含模型描述及部分示例代码）
最新发布
11-25
内容概要：本文详细介绍了一个基于C++的影视数据可视化系统的设计与实现，旨在应对影视行业海量、多源数据带来的分析挑战。系统利用C++的高性能优势，实现了大规模数据的高效处理与实时更新，支持多维度数据分析，涵盖票房、用户评价、社交媒体热度等，并通过柱状图、折线图、热力图、词云等多种可视化方式直观展示数据。项目强调用户友好的界面设计、跨平台兼容性、可扩展性与可定制性，结合创新的交互设计，提升用户体验与决策效率。系统不仅服务于影视创作者和营销团队，也为行业数字化转型和创新发展提供数据驱动的支持。; 适合人群：具备一定C++编程基础，从事数据分析、可视化开发或影视行业技术研究的研发人员、软件工程师及高校学生。; 使用场景及目标：①学习如何利用C++构建高性能数据可视化系统；②掌握多源数据融合、实时处理与图形渲染的技术方案；③为影视项目提供数据支持，优化内容创作与市场策略； 阅读建议：建议结合文中提到的模型设计与示例代码进行实践，重点关注数据处理流程、可视化模块实现及系统架构设计，同时可联系作者获取完整代码与GUI资源以加深理解。
CSS插入图片方法[可运行源码]
11-25
本文详细介绍了在CSS中插入图片的多种方法，包括使用background-image属性和background简写属性。通过设置不同的背景属性值，如background-color、background-position、background-size等，可以灵活控制背景图片的显示效果。文章还提供了具体的HTML示例代码，展示了如何在实际项目中应用这些属性。此外，还解释了背景图像默认位于元素左上角并在水平和垂直方向上重复的特性，以及如何通过background-repeat属性调整平铺方式。
jQuery与HTML设置只读/禁用属性[项目代码]
11-25
本文详细介绍了在jQuery和HTML中如何设置和移除表单元素的只读（readonly）和禁用（disabled）属性。在jQuery部分，通过attr()和removeAttr()方法演示了属性的动态操作，并对比了readonly与disabled的区别：disabled会阻止元素获取焦点且表单提交时排除该字段，而readonly仅限制编辑但仍可聚焦和提交。HTML部分列举了三种实现方式（onfocus=this.blur()、readonly、disabled），并附代码示例说明其视觉效果及交互差异（如灰色显示、Tab键切换等）。最后指出两者可结合使用，并补充了CSS屏蔽输入的技巧。
SQL编码规范指南[项目源码]
11-25
本文详细介绍了SQL编码规范的重要性及其具体实施方法。规范化的SQL代码能显著提升可读性、便于问题定位和团队协作。文章强调了大小写的正确使用、单引号与双引号的应用场景、缩进对齐原则、禁止使用SELECT *操作、注释的添加规范以及子句的排版规则等关键点。此外，还提供了表别名的命名建议、字段逗号放置位置等实用技巧，旨在帮助开发者编写清晰、整齐、结构化的SQL代码，从而提升编程效率和代码质量。
Layui输入事件监听[代码]
11-25
本文详细介绍了Layui框架中各种表单元素的输入事件监听方法，包括单选框、复选框、下拉菜单、输入框内容变动以及提交按钮的监听。通过示例代码展示了如何实时获取用户输入的值、监听表单元素的变化以及处理提交事件。此外，还提供了带注释的代码片段，帮助开发者理解每个事件监听器的具体功能和用法。这些方法可以广泛应用于表单验证、动态数据更新等场景，提升用户交互体验。
UAC-BOF-Bonanza[项目源码]
11-25
UAC-BOF-Bonanza is a GitHub repository that compiles various UAC (User Account Control) bypass techniques, weaponized as Beacon Object Files (BOFs). The project includes a module for the Havoc C2 Framework and extension.json files for Sliver C2, enabling users to leverage these bypass methods in red team operations. Techniques include exploiting elevated COM objects, registry modifications, DLL hijacking, and SSPI token forgery. The repository provides detailed usage instructions, OpSec considerations, and credits to original researchers. All bypasses were tested on Windows 10 and 11, though they may be detected by SOCs and EDR solutions. The project is licensed under GPL-3.0 and includes standalone implementations for each bypass.
ImportError Traceback (most recent call last) File D:\anaconda3\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py:73 72 try: ---> 73 from tensorflow.python._pywrap_tensorflow_internal import * 74 # This try catch logic is because there is no bazel equivalent for py_extension. 75 # Externally in opensource we must enable exceptions to load the shared object 76 # by exposing the PyInit symbols with pybind. This error will only be 77 # caught internally or if someone changes the name of the target _pywrap_tensorflow_internal. 78 79 # This logic is used in other internal projects using py_extension. ImportError: DLL load failed while importing _pywrap_tensorflow_internal: 动态链接库(DLL)初始化例程失败。 During handling of the above exception, another exception occurred: ImportError Traceback (most recent call last) Cell In[12], line 5 3 import numpy as np 4 import pandas as pd ----> 5 from keras.models import Sequential, load_model 6 from tensorflow.keras import utils 7 from keras.preprocessing.sequence import pad_sequences File ~\AppData\Roaming\Python\Python311\site-packages\keras\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras import _tf_keras as _tf_keras 8 from keras import activations as activations 9 from keras import applications as applications File ~\AppData\Roaming\Python\Python311\site-packages\keras\_tf_keras\__init__.py:1 ----> 1 from keras._tf_keras import keras File ~\AppData\Roaming\Python\Python311\site-packages\keras\_tf_keras\keras\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras import activations as activations 8 from keras import applications as applications 9 from keras import callbacks as callbacks File ~\AppData\Roaming\Python\Python311\site-packages\keras\activations\__init__.py:7 1 """DO NOT EDIT. 2 3 This file was autogenerated. Do not edit it by hand, 4 since your modifications would be overwritten. 5 """ ----> 7 from keras.src.activations import deserialize as deserialize 8 from keras.src.activations import get as get 9 from keras.src.activations import serialize as serialize File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\__init__.py:1 ----> 1 from keras.src import activations 2 from keras.src import applications 3 from keras.src import backend File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\activations\__init__.py:3 1 import types ----> 3 from keras.src.activations.activations import celu 4 from keras.src.activations.activations import elu 5 from keras.src.activations.activations import exponential File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\activations\activations.py:1 ----> 1 from keras.src import backend 2 from keras.src import ops 3 from keras.src.api_export import keras_export File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\__init__.py:1 ----> 1 from keras.src.backend.config import backend 3 if backend() == "torch": 4 # When using the torch backend, 5 # torch needs to be imported first, otherwise it will segfault 6 # upon import. 7 import torch File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\config.py:448 445 else: 446 _NNX_ENABLED = False --> 448 set_nnx_enabled(_NNX_ENABLED) File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\config.py:249, in set_nnx_enabled(value) 247 def set_nnx_enabled(value): 248 global _NNX_ENABLED --> 249 from keras.src.backend.common import global_state 251 _NNX_ENABLED = bool(value) 252 if _NNX_ENABLED: File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\common\__init__.py:2 1 from keras.src.backend.common import backend_utils ----> 2 from keras.src.backend.common.dtypes import result_type 3 from keras.src.backend.common.variables import AutocastScope 4 from keras.src.backend.common.variables import Variable as KerasVariable File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\common\dtypes.py:5 3 from keras.src.api_export import keras_export 4 from keras.src.backend import config ----> 5 from keras.src.backend.common.variables import standardize_dtype 7 BOOL_TYPES = ("bool",) 8 INT_TYPES = ( 9 "uint8", 10 "uint16", (...) 16 "int64", 17 ) File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\backend\common\variables.py:12 10 from keras.src.backend.common.stateless_scope import in_stateless_scope 11 from keras.src.utils.module_utils import tensorflow as tf ---> 12 from keras.src.utils.naming import auto_name 15 class Variable: 16 """Represents a backend-agnostic variable in Keras. 17 18 A `Variable` acts as a container for state. It holds a tensor value and can (...) 89 ``` 90 """ File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\utils\__init__.py:1 ----> 1 from keras.src.utils.audio_dataset_utils import audio_dataset_from_directory 2 from keras.src.utils.dataset_utils import split_dataset 3 from keras.src.utils.file_utils import get_file File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\utils\audio_dataset_utils.py:4 1 import numpy as np 3 from keras.src.api_export import keras_export ----> 4 from keras.src.utils import dataset_utils 5 from keras.src.utils.module_utils import tensorflow as tf 6 from keras.src.utils.module_utils import tensorflow_io as tfio File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\utils\dataset_utils.py:10 7 import numpy as np 9 from keras.src import backend ---> 10 from keras.src import tree 11 from keras.src.api_export import keras_export 12 from keras.src.utils import file_utils File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\tree\__init__.py:1 ----> 1 from keras.src.tree.tree_api import assert_same_paths 2 from keras.src.tree.tree_api import assert_same_structure 3 from keras.src.tree.tree_api import flatten File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\tree\tree_api.py:13 11 from keras.src.tree import torchtree_impl as tree_impl 12 elif optree.available: ---> 13 from keras.src.tree import optree_impl as tree_impl 14 elif dmtree.available: 15 from keras.src.tree import dmtree_impl as tree_impl File ~\AppData\Roaming\Python\Python311\site-packages\keras\src\tree\optree_impl.py:13 11 # Register backend-specific node classes 12 if backend() == "tensorflow": ---> 13 from tensorflow.python.trackable.data_structures import ListWrapper 14 from tensorflow.python.trackable.data_structures import _DictWrapper 16 try: File D:\anaconda3\Lib\site-packages\tensorflow\python\trackable\data_structures.py:26 22 except ImportError: 23 # Fall back to the build-time dependency if the system package is not available. 24 from .....third_party import wrapt # pylint: disable=relative-beyond-top-level ---> 26 from tensorflow.python.eager import def_function 27 from tensorflow.python.eager import function as defun 28 from tensorflow.python.ops import variables File D:\anaconda3\Lib\site-packages\tensorflow\python\eager\def_function.py:24 21 from tensorflow.python.eager.polymorphic_function.eager_function_run import functions_run_eagerly 23 # tf.function Classes ---> 24 from tensorflow.python.eager.polymorphic_function.polymorphic_function import Function 25 from tensorflow.python.eager.polymorphic_function.polymorphic_function import function 27 # Private attributes File D:\anaconda3\Lib\site-packages\tensorflow\python\eager\polymorphic_function\polymorphic_function.py:74 72 from google.protobuf.message import DecodeError 73 from tensorflow.core.framework import attr_value_pb2 ---> 74 from tensorflow.core.function import trace_type 75 from tensorflow.core.function.capture import capture_container 76 from tensorflow.core.function.polymorphism import function_cache File D:\anaconda3\Lib\site-packages\tensorflow\core\function\trace_type\__init__.py:28 1 # Copyright 2021 The TensorFlow Authors. All Rights Reserved. 2 # 3 # Licensed under the Apache License, Version 2.0 (the "License"); (...) 13 # limitations under the License. 14 # ============================================================================== 15 """Trace-time type system for tf.function (TraceType). 16 17 Trace-time types describe things like tf.function signatures and type (...) 25 Other implementations of TraceType include tf.TypeSpec and its subclasses. 26 """ ---> 28 from tensorflow.core.function.trace_type.default_types import register_tensor_type 29 from tensorflow.core.function.trace_type.default_types import Weakref 30 from tensorflow.core.function.trace_type.serialization import deserialize File D:\anaconda3\Lib\site-packages\tensorflow\core\function\trace_type\default_types.py:26 24 from tensorflow.core.function.trace_type import serialization 25 from tensorflow.core.function.trace_type import util ---> 26 from tensorflow.python.types import trace 28 # Register the TraceType of Tensor (aka TensorSpec) to avoid cyclic dependency. 29 TENSOR = None File D:\anaconda3\Lib\site-packages\tensorflow\python\types\trace.py:34 31 from typing_extensions import Protocol 32 from typing_extensions import runtime_checkable ---> 34 from tensorflow.python.types import core 35 from tensorflow.python.util.tf_export import tf_export 36 from tensorflow.tools.docs import doc_controls File D:\anaconda3\Lib\site-packages\tensorflow\python\types\core.py:28 23 import numpy as np 25 from tensorflow.python.types import doc_typealias ---> 28 from tensorflow.python import pywrap_tensorflow # pylint: disable=unused-import, g-bad-import-order 29 from tensorflow.python.util.tf_export import tf_export 31 # pylint:disable=g-import-not-at-top File D:\anaconda3\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py:88 86 sys.setdlopenflags(_default_dlopen_flags) 87 except ImportError: ---> 88 raise ImportError( 89 f'{traceback.format_exc()}' 90 f'\n\nFailed to load the native TensorFlow runtime.\n' 91 f'See https://www.tensorflow.org/install/errors ' 92 f'for some common causes and solutions.\n' 93 f'If you need help, create an issue ' 94 f'at https://github.com/tensorflow/tensorflow/issues ' 95 f'and include the entire stack trace above this error message.') ImportError: Traceback (most recent call last): File "D:\anaconda3\Lib\site-packages\tensorflow\python\pywrap_tensorflow.py", line 73, in <module> from tensorflow.python._pywrap_tensorflow_internal import * ImportError: DLL load failed while importing _pywrap_tensorflow_internal: 动态链接库(DLL)初始化例程失败。 Failed to load the native TensorFlow runtime. See https://www.tensorflow.org/install/errors for some common causes and solutions. If you need help, create an issue at https://github.com/tensorflow/tensorflow/issues and include the entire stack trace above this error message.
10-29
`ImportError: DLL load failed while importing _pywrap_tensorflow_internal: 动态链接库(DLL)初始化例程失败` 错误通常与 TensorFlow 依赖的动态链接库（DLL）未能正确加载有关。以下是一些可能的解决方法： ...
评论
添加红包

请填写红包祝福语或标题

个

红包个数最小为10个

元

红包金额最低5元

当前余额3.43元 前往充值 >
需支付：10.00元
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付元
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明：

1.余额是钱包充值的虚拟货币，按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载，可以购买VIP、付费专栏及课程。

余额充值