assignmentutor-lab™ 为您的留学生涯保驾护航 在代写面向对象的系统设计Object-Oriented Systems Design方面已经树立了自己的口碑, 保证靠谱, 高质且原创的统计Statistics代写服务。我们的专家在代写面向对象的系统设计Object-Oriented Systems Design方面经验极为丰富，各种代写面向对象的系统设计Object-Oriented Systems Design相关的作业也就用不着说。

• Statistical Inference 统计推断
• Statistical Computing 统计计算
• (Generalized) Linear Models 广义线性模型
• Statistical Machine Learning 统计机器学习
• Longitudinal Data Analysis 纵向数据分析
• Foundations of Data Science 数据科学基础

## 电子工程代写|面向对象的系统设计代写Object-Oriented Systems Design代考|Characterizing the Design

Independently of our convictions about software metrics, every time we analyze or talk about a software system, we want to obtain an impression of the size and complexity of the software system to be able to characterize it. Some people like to express the size of a system in terms of lines of code, others use the number of classes, and even others only measure the amount of source code in megabytes.

These numbers are nothing more than the values of some basic metrics. For object-oriented systems the most common ones are the lines of code, the number of classes, the number of packages or subsystems, the number of operations (methods), etc.

Unfortunately, after getting such numbers in isolation, we still have trouble clearly characterizing the system. How come? There are several causes:

• Unbalanced characterization. The characterization is unbalanced because metrics only partially cover the aspects of interest. How faithful to object-oriented principles is the design of a system given the fact that it consists of 500 classes and 25,000 lines of code?
• Misused metrics. Knowing that a system has 500 classes does not tell us how large the system is because the classes in question could all be very large or very small. Neither do we know how complex a system is, if we know that it has 25,000 lines of code. Furthermore, how is a line of code defined? Do we count comments? Do we count lines containing curly brackets or semi-colons?
• Uncorrelated metrics. A lot of information slips through our fingers because it is not revealed by the raw numbers but by the proportions (ratios) between the raw values. Assume again that a system has 500 classes and 50,000 lines of code. Is something striking?

## 电子工程代写|面向对象的系统设计代写Object-Oriented Systems Design代考|The Overview Pyramid

The overview of an object-oriented system must necessarily include metrics that reflect three main aspects:

1. Size and complexity. We want to understand how big and how complex a system is.
2. Coupling. The core of the object-oriented paradigm are objects that encapsulate data and that collaborate at run-time with each other to make the system perform its functionalities. We want to know to which extent classes (the creators of the objects) are coupled with each other.
1. Inheritance. A major asset of object-oriented languages is the ease of code reuse that is possible by creating classes that inherit func tionality from their superclasses. We want to understand how much the concept of inheritance is used and how well it is used.
To understand these three aspects we introduce the Overview Pyramid, which is an integrated, metrics-based means to both describe and characterize the overall structure of an object-oriented system, by quantifying the aspects of complexity, coupling and usage of inheritance.

The basic idea behind the Overview Pyramid is to put together in one place the most significant measurements about an objectoriented system, so that an engineer can see and interpret in one shot everything that is needed to get a first impression about the system. The Overview Pyramid is a graphical representation of metrics values which can be visually interpreted. Yet, it is not a metrics visualization (in the sense of Sect. 2.2). From this point of view the Overview Pyramid is a graphical template for presenting (and interpreting) system-level measurements in a unitary manner. In order to Polymetric Views (see Sect. 3.2).

# 面向对象的系统设计代考

## 电子工程代写|面向对象的系统设计代写Object-Oriented Systems Design代考|Characterizing the Design

• 不平衡的表征。表征是不平衡的，因为指标仅部分涵盖了感兴趣的方面。考虑到系统由 500 个类和 25,000 行代码组成，它的设计对面向对象原则的忠诚度如何？
• 滥用的指标。知道一个系统有 500 个类并不能告诉我们系统有多大，因为所讨论的类都可能非常大或非常小。如果我们知道一个系统有 25,000 行代码，我们也不知道它有多复杂。此外，如何定义一行代码？我们计算评论吗？我们是否计算包含大括号或分号的行？
• 不相关的指标。很多信息从我们的手指间溜走，因为它不是由原始数字而是由原始值之间的比例（比率）揭示的。再次假设一个系统有 500 个类和 50,000 行代码。有什么惊人的吗？

## 电子工程代写|面向对象的系统设计代写Object-Oriented Systems Design代考|The Overview Pyramid

1. 规模和复杂性。我们想了解系统的规模和复杂程度。
2. 耦合。面向对象范式的核心是封装数据并在运行时相互协作以使系统执行其功能的对象。我们想知道类（对象的创建者）在何种程度上相互耦合。
3. 遗产。面向对象语言的一个主要资产是代码重用的简单性，这可以通过创建从其超类继承功能性的类来实现。我们想了解继承的概念使用了多少以及使用得如何。
为了理解这三个方面，我们介绍了概览金字塔，它是一种集成的、基于度量的方法，通过量化复杂性、耦合和继承的使用等方面来描述和表征面向对象系统的整体结构。

## 有限元方法代写

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## MATLAB代写

MATLAB 是一种用于技术计算的高性能语言。它将计算、可视化和编程集成在一个易于使用的环境中，其中问题和解决方案以熟悉的数学符号表示。典型用途包括：数学和计算算法开发建模、仿真和原型制作数据分析、探索和可视化科学和工程图形应用程序开发，包括图形用户界面构建MATLAB 是一个交互式系统，其基本数据元素是一个不需要维度的数组。这使您可以解决许多技术计算问题，尤其是那些具有矩阵和向量公式的问题，而只需用 C 或 Fortran 等标量非交互式语言编写程序所需的时间的一小部分。MATLAB 名称代表矩阵实验室。MATLAB 最初的编写目的是提供对由 LINPACK 和 EISPACK 项目开发的矩阵软件的轻松访问，这两个项目共同代表了矩阵计算软件的最新技术。MATLAB 经过多年的发展，得到了许多用户的投入。在大学环境中，它是数学、工程和科学入门和高级课程的标准教学工具。在工业领域，MATLAB 是高效研究、开发和分析的首选工具。MATLAB 具有一系列称为工具箱的特定于应用程序的解决方案。对于大多数 MATLAB 用户来说非常重要，工具箱允许您学习应用专业技术。工具箱是 MATLAB 函数（M 文件）的综合集合，可扩展 MATLAB 环境以解决特定类别的问题。可用工具箱的领域包括信号处理、控制系统、神经网络、模糊逻辑、小波、仿真等。

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