Lecture 2_Introduction to Software Engineering
大学课程名称英文大全
公共基础课专业外语Specialized English大学物理College Physics马克思主义哲学原理(认识论) Principle of Marxist Philosophy(Epistemology) 邓小平理论Deng Xiaoping Theory毛泽东思想研究Study on Mao Zedong Thought毛泽东政治思想研究Research on Mao ZeDong Political Thought2毛泽东哲学思想研究Research of Mao Zedong's Philosophy Thought体育Physical Education思想品德修养Cultivation of Ideological Morality形势政策教育Teaching of Situation and Policy军事理论Military Theory政治经济学Political Economics高等数学含现性代数Advanced Mathematics (Including Linear Algebra)概率论与数理统计Probability and Mathematical Statistics计算机应用基础Basics of Computer Applications数据库概论Introduction to Database大学英语College English大学语文(文科) The University Language and Literature (Liberal arts)大学语文(理科) The University Language and Literature (Science)工商管理西方经济学概论Introduction to Western Economics管理心理学Psychology of Management管理学原理Principles of Management Science统计学原理Principles of Statistics会计学原理Principles of Accounting管理信息系统Management Information Systems信息检索Information Retrieval经济法学Economic law企业战略Enterprise Strategy财政学Public Finance货币银行学Monetary Economics and Banking国际金融International Finance国际贸易International Trade生产管理Productive Management市场营销学Marketing财务管理Financial Management管理思想史History of Management Thought工业经济管理Industrial Economy Management管理会计Managerial Accounting运筹学Operations Research税收学Taxation计划项目评估Evaluation of Planning items产业经济管理学Management Theories of Industrial Economy 信息经济学Information Economics电子信息科学与技术专业数学物理方法Mathematical Methods of Physics概率论与数理统计Probability and Mathematical Statistics普通物理General Physics普通物理实验Experiments in General Physics电路分析基础Fundamentals of Circuit Analysis模拟电路实验Experiments in Analogue Circuit数字电路与逻辑设计Digital Circuits and Logical Programming数字电路实验Experiments in Digital Circuit微机原理及应用Computer Principles and Applications微机实验Experiment in Computer信号与系统Signals and Systems通信系统与技术Communication Systems and Techniques电磁场理论The Theory of Electromagnetic Fields计算机应用基础Basics of Computer Applications计算机语言及应用Computer Language and Application单片机应用Application of Single Chip Processor电子学Electronics计算机信息系统Computer Information System数字信号处理Digital Signal Processing数字图象处理Digital Image Processing自动控制原理Principles of Automatic Control通信系统与技术Communication Systems and Techniques电磁场与微波技术Electromagnetic Fields and Microwave Techniques 微波实验Experiments in Microwave光纤通信技术Communication Technique of Optical Fibre法学宪法学Constitution of China民法学Civil Law of China刑法学Criminal Law经济法学Economic law国际经济法学International Economic Law民事诉讼法Civil Procedure中国法制史History of Chinese Law刑事诉讼法学Criminal Procedure行政法学Administrative Law国际私法Private International Law国际公法Public International Law外国民商法学Civil Law and Commercial Law of Foreign Countries 知识产权概论Introduction to Intellectual Property国际经济法学International Economic Law外国法制史History of Foreign Law司法文书Judicial Documents法医学Medical Jurisprudence刑事诉讼法学Criminal Procedure律师公证Lawyer Notarization中国法律思想史History of Legal Thoughts of China外国法律思想史History of Legal Thoughts of Foreign Countries环境法学概论Introduction to Environmental Law犯罪心理学Criminal Psychology房地产法规Real Estate Laws and Regulations婚姻家庭史History of Marriage and Family会计概率论与数理统计Probability and Mathematical Statistics西方经济学概论Introduction to Western Economics管理学原理Principles of Management Science统计学原理Principles of Statistics会计学原理Principles of Accounting管理信息系统Management Information Systems经济法学Economic law财务会计Financial Accounting成本会计Cost Accounting会计电算化Computer Application in Accounting审计学Auditing管理会计Managerial Accounting财务管理Financial Management税收法Taxation Law银行经营管理学Banking Management保险学Insurance信息经济学Information Economics证券投资学Securities Investment Theories产业经济管理学Management Theories of Industrial Economy财务报表分析Financial Statements Analysis资产评估Assets Evaluation计算机科学与技术离散数学Discrete Mathematics概率统计Probability Statistics数字逻辑电路Digital Logical Circuit数字逻辑电路实验Experiments in Digital Logical Circuit数字逻辑设计实验Experiments in Digital and Logical Programming 汇编语言程序设计Assembly Language Programming数据结构Data StructurePASCAL语言PASCAL Programming Language操作系统Operating System编译原理Principles of Compiling面向对象程序设计Object-oriented Programming数据库原理与应用Database Principles and Applications接口技术Interface Techniques软件工程概论Introduction to Software Engineering算法设计与分析The Design and Analysis of AlgorithmC程序设计语言C Programming Language计算机图形学Computer Graphics计算机系统结构实验Experiments in Computer Organization 多媒体技术基础Basics of Computer Multimedia Technology 人工智能导论Introduction to Artificial Intelligence数据库设计Database Design数据库技术与应用Database Technology and ApplicationJA V A程序设计语言JA V A Programming LanguagesUNIX和C语言UNIX and C Language数理逻辑Mathematical Logic近世代数Abstract Algebra新闻学基础写作Creative Writing传播学Mass Communication新闻事业管理Journalism Management新闻理论Theories of Journalism中国新闻史History of Chinese Journalism外国新闻史History of Foreign Journalism新闻采访学Interviewing in Journalism新闻写作学Writing in Journalism新闻编辑学Editing in Journalism新闻摄影Press Photography广播电视学Television Broadcasting Science新闻评论写作Review and Writing in Journalism新闻传播与广告学News Communications and Advertisement 公共关系理论与实务Theory and Practice of Public Relations 社会学概论Introduction to Sociology文学概论Introduction to Literary Theory心理学概论Introduction to Psychology美学原理Principles of Aesthetics统计学概率论与数理统计Probability and Mathematical Statistics数据库原理与应用Database Principles and Applications西方经济学概论Introduction to Western Economics管理心理学Psychology of Management管理学原理Principles of Management Science统计学原理Principles of Statistics会计学原理Principles of Accounting管理信息系统Management Information Systems经济法学Economic law统计学Statistics国民经济核算National Economic Accounting运筹学Operations Research管理会计Managerial Accounting信息经济学Information Economics统计学Statistics税收学Taxation审计学Auditing金融学专业经济法学Economic law管理学原理Principles of Management Science 微观经济学Microeconomics宏观经济学Macroeconomics基础会计学Basic Accounting管理信息系统Management Information Systems 电子商务Electronic Commercial Affairs财务会计Financial Accounting市场营销学Marketing国际金融International Finance国际贸易International Trade人力资源管理Human Resources Management 货币银行学Monetary Economics and Banking 财政学Public Finance证券投资学Securities Investment Theories专业英语Specialized English保险经营学Insurance Management Science投资项目经济分析Economic Analysis of Investment Items国际结算International Settlements国际商法International Commercial Law国际技术贸易International Technology Transfer Transactions国际企业管理International Enterprise Management投资决策理论与方法Theories and Methods of Investment Policy-making 转载请注明出自应届生求职招聘论坛本贴地址4001-1-1。
SE-121《软件工程专业导论》课程教学大纲
Laboratory Sessions
学时合计
34
Total Hours
Prof. Hui-you CHANG Email : isschy@ Homepage : /informationsystem/Article.aspx?id=3659
常会友教授、李文军教授、周晓聪副教授、余阳副教授、衣杨副教授、刘宁副教授
Prof. Hui-you CHANG, Prof. Wen-jun LI, A/Prof. Yang YU, A/Prof. Xiao-cong ZHOU, A/Prof.
Yang YI, A/Prof. Ning LIU 每班配置 1 名 TA，负责批改作业、实验报告并指导实验过程。
-1-
先修课程 Prerequisites
后续课程 Successive
Courses
教材 Textbook
教学参考书 References
教学方法 Approach 理论教学内容 Lectures
Introduction to Software Engineering is a fundamental course for those students who major in software engineering. This course focuses on the topics of the knowledge body, discipline foundations, and professional requirements for software engineers. Basic concepts and principles in computer science are covered in this course, including: computation models, digital systems, digital logic and integrated circuits, computer hardware and software, computer languages and programs, data management, and information processing. The students are also equipped with the fundamentals, methodologies, histories and disciplines of computing science. Furthermore, basic concepts and principles of software engineering and project management are also introduced.
Introduction of SE
is concerned with all aspects of software production. Software engineers should adopt a systematic and organised approach to their work and use appropriate tools and techniques depending on the problem to be solved, the development constraints and the resources available.
Generic - developed to be sold to a range of different
customers e.g. PC software such as Excel or Word. Bespoke (custom) - developed for a single customer according to their specification.
An Introduction to Software Engineering
Objectives
To introduce software engineering and to
explain its importance To set out the answers to key questions about software engineering
Topics covered
Introduction of software engineering FAQs about software engineering Trends in software engineering
ccf计算机软件能力认证 参考书籍
ccf计算机软件能力认证参考书籍计算机软件能力认证（Computer Software Capability Certification，简称CCF）是一项针对计算机软件人员的职业能力认证。
通过参加CCF考试并取得认证资格，可以证明个人在软件开发、架构设计、系统维护以及相关领域的专业能力。
为了帮助考生充分准备CCF考试，下面将介绍一些参考书籍，供考生参考。
1. 《软件工程导论》（Introduction to Software Engineering）《软件工程导论》是一本系统介绍软件工程概念、原理、方法和实践的经典教材。
这本书从软件工程的基本概念出发，讲解了软件开发的整个过程，包括需求分析、设计、开发、测试、部署和维护等各个环节。
对于CCF认证考试来说，掌握软件工程的基本原理是非常重要的，这本书可以帮助考生建立系统的软件工程知识体系。
2. 《设计模式：可复用面向对象软件的基础》（Design Patterns: Elements of Reusable Object-Oriented Software）《设计模式：可复用面向对象软件的基础》是由四位软件工程师合著的一本著名书籍。
这本书总结了23种常见的设计模式，包括创建型、结构型和行为型模式，对于面向对象软件开发非常有指导意义。
CCF考试中，设计模式也是一个重要的考点，考生需要熟悉各种设计模式的定义、特点和适用场景。
3. 《代码大全》（Code Complete）《代码大全》是一本关于软件构建的经典书籍，着重介绍了如何编写高质量的软件代码。
这本书包含了大量的编程技巧、实用建议和规范，旨在帮助开发人员提高代码质量和开发效率。
CCF认证考试除了要求考生具备良好的软件设计能力，还要求考生具备扎实的编程能力，这本书可以帮助考生提升编码水平。
4. 《操作系统导论》（Operating System Concepts）《操作系统导论》是一本广泛使用的操作系统教材，介绍了操作系统的基本概念、原理和实现技术。
计算机专业英语第三版教学课件Unit5 Software Engineering
布朗先生：您好！中华计算机公司。我能为您做些什么？
Linda: Hello, Mr. Brown. It is Linda. Got a minute?
琳达：您好，布朗先生。我是琳达。您有时间吗？
Mr. Brown: I see your point. If we have to spend more time on developing the second version, we’ll have to adjust the schedule. People need to know that we have adjusted the project development plan as soon as possible. Do you want me to call the project manager?
Look and Learn Dialogue Reading Learn More New Words and Phrases
A software development project organization.
Lesson 14
Unit 5
Look and Learn Dialogue Reading Learn More New Words and Phrases
Mr. Brown: Yes.We planned to put the two versions in the same development process. Well, what kind of problem are you having now?
布朗先生：是的。我们计划在同一个开发过程中投入两个版本。那您现在遇到什么问题了？
电子商务讲解课件(英文)Lecture
Effective channels for customers to get help and resolve issues.
03
E-commerce Businesses
Marketplace
Marketplace Amazon Alibaba eBay
A platform that brings together buyers and sellers to facilitate transactions.
A crowdfunding platform that allows individuals or groups to raise funds for personal causes or charitable
projects.
Airbnb
A peer to peer e-commerce platform that allows
01
02
03
起始阶段
20世纪90年代初，电子商 务出现，以静态网页展示 产品信息。
发展阶段
20世纪90年代末至21世 纪初，电子商务平台兴起 ，在线购物逐渐普及。
成熟阶段
21世纪中期至今，移动支 付、社交电商、跨境电商 等多元化模式涌现。
Types of E-commerce
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B2B (Business-to-Business) ：企业与企业之间的电子商务
Bitcoin, Ethereum, etc., used for secure, decentralized transactions.
Delivery and Logistics
In-store pickup
软件工程相关书籍
软件工程相关书籍软件工程是一门关于如何以系统化、规范化和可重复使用的方式开发、维护和管理软件的学科。
在软件工程领域中，有许多经典的书籍提供了丰富的知识和实践经验。
本文将介绍一些与软件工程相关的书籍，这些书籍涵盖了软件开发的各个方面，从项目管理到软件测试等。
1. 《软件工程导论》 (Introduction to Software Engineering)这本书由Ian Sommerville撰写，详细介绍了软件工程的基本概念和原理。
它介绍了软件开发的生命周期模型、需求工程、软件设计和实现、软件测试和维护等内容。
本书为初学者提供了软件工程的全面介绍。
2. 《人月神话》 (The Mythical Man-Month)由Fred Brooks撰写，这本经典书籍探讨了软件开发中的人力资源管理问题。
它介绍了Brooks' Law，即“增加人手会导致进度更加落后”，并提供了解决这一问题的方法和经验教训。
这本书是理解软件工程团队合作和项目管理的必读之作。
3. 《代码大全》 (Code Complete)由Steve McConnell撰写，这本书提供了许多实用的编程技巧和最佳实践。
它涵盖了软件开发的各个方面，包括代码编写、测试、调试、文档编写等。
这本书适合程序员和软件工程师，帮助他们编写高质量的、可维护的代码。
4. 《软件测试的艺术》 (The Art of Software Testing) Glenford J. Myers撰写了这本经典的软件测试书籍。
它详细介绍了软件测试的基本原理、测试技术和测试策略。
这本书探讨了黑盒测试、白盒测试、单元测试、集成测试等各个方面的内容，对于提高软件质量和可靠性非常有价值。
5. 《敏捷软件开发原则、模式与实践》 (Agile Software Development: Principles, Patterns, and Practices)该书由Robert C. Martin撰写，介绍了敏捷开发的基本原则和实践。
fundamentals of software architecture 笔记总结
fundamentals of software architecture 笔记总结Fundamentals of Software Architecture: A SummarySoftware architecture plays a critical role in the development of any software system. It provides a blueprint for designing, implementing, and maintaining the overall structure of the software. In this article, we will delve into the fundamentals of software architecture and explore its key components and best practices.1. Introduction to Software ArchitectureSoftware architecture is the process of defining a structured solution to meet technical and operational requirements. It involves making strategic decisions about software components, interactions, and behaviors to ensure a system's desired qualities such as reliability, scalability, and maintainability.2. Key Components of Software Architecture2.1. Architectural StylesArchitectural styles define the overall structure and behavior of a software system. Examples of popular architectural styles include client-server, layered, microservices, and event-driven architectures. Each style has its unique characteristics and is suited for specific types of applications.2.2. Components and ConnectorsComponents refer to the different parts of a system that perform specific functions. Connectors, on the other hand, define how thesecomponents communicate and interact with each other. Examples of connectors include HTTP, message queues, and databases. Proper identification and understanding of components and connectors are crucial for designing an effective software architecture.2.3. Design PrinciplesDesign principles guide software architects in making sound architectural decisions. These principles include modularity, separation of concerns, encapsulation, and abstraction. Adhering to these principles results in a more modular, maintainable, and flexible software architecture.3. Best Practices in Software Architecture3.1. Scalability and PerformanceA well-designed software architecture should be scalable to handle increased workload and maintain optimal performance. This can be achieved through techniques such as load balancing, caching, and vertical or horizontal scaling.3.2. SecuritySecurity is a crucial aspect of software architecture. Architects must take into account security measures such as authentication, authorization, and secure communication protocols during the design phase to protect the system from potential threats.3.3. MaintainabilityThe architecture should be designed with maintainability in mind. This includes modularizing the system into smaller components, adhering tocoding standards, and providing proper documentation. A maintainable architecture enables easier bug fixing, enhancements, and future system updates.4. Tools and TechnologiesVarious tools and technologies are available to assist in software architecture design and implementation. These include modeling languages like UML (Unified Modeling Language), design patterns, and architectural frameworks such as TOGAF (The Open Group Architecture Framework) and Zachman Framework.5. Case StudiesCase studies provide real-life examples of successful software architectures. Analyzing case studies can help understand the practical application of architectural concepts and learn from the experiences of others.6. ConclusionIn conclusion, software architecture is a fundamental aspect of software development, encompassing the design, structure, and behavior of a software system. By following best practices and understanding key components, architects can create robust, scalable, and maintainable architectures that meet the requirements of modern software systems.Remember, software architecture is a vast field, and this article provides only a summary of its fundamentals. Further exploration and learning are essential to master this important discipline in the software development lifecycle.。
lecture2
MASSACHVSETTS INSTITVTE OF TECHNOLOGYDepartment of Electrical Engineering and Computer Science6.081—Introduction to EECS ISpring Semester,2007Lecture2NotesThe Functional StyleIn the functional programming style,one tries to use a very small set of primitives and means of combination.We’ll see that recursion is a very powerful primitive,which could allow us to dispense with all other looping constructs(while and for)and result in code with a certain beauty. Another element of functional programming style is the idea of functions asfirst-class objects.That means that we can treat functions or procedures in much the same way we treat numbers or strings in our programs:we can pass them as arguments to other procedures and return them as the results from procedures.This will let us capture important common patterns of abstraction and will also be an important element of object-oriented programming.BasicsBut let’s begin at the beginning.The primitive elements in the functional programming style are basic functions.They’re combined via function composition:so,for instance f(x,g(x,2))is a composition of functions.To abstract away from the details of an implementation,we can define a functiondef square(x):return x*xOrdef average(a,b):return(a+b)/2.0And now,having defined those functions,we can use them exactly as if they were primitives.So, for example,we could compute the mean square of two values asaverage(square(7),square(11))Here’s a more interesting example.What if you wanted to compute the square root of a number? Here’s a procedure that will do it:def sqrt(x):def goodEnough(guess):return abs(x-square(guess))<.0001guess=1.0while not goodEnough(guess):guess=average(guess,x/guess)return guess>>>sqrt(2)1.4142156862745097This is an ancient algorithm,due to Hero of Alexandria.1It is an iterative algorithm:it starts with a guess about the square root,and repeatedly asks whether the guess is good enough.It’s good enough if,when we square the guess,we are close to the number,x,that we’re trying to take the square root of.If the guess isn’t good enough,we need to try to improve it.We do that by making a new guess,which is the average of the original guess and x/guess.How do we know that this procedure is ever going tofinish?We have to convince ourself that, eventually,the guess will be good enough.The mathematical details of how to make such an argument are more than we want to get into here,but you should at least convince yourself that the new guess is closer to x than the previous one was.This style of computation is generally quite useful.We’ll see later in this chapter how to capture this common pattern of function definition and re-use it easily.Note also that we’ve defined a function,goodEnough,inside the definition of another function.We did it because it’s a function that we don’t expect to be using elsewhere;it’s just here to help out in sqrt.We’ll study this style of definition in detail in the next chapter.For now,it’s important to notice that the variable x inside goodEnough is the same x that was passed into the sqrt function. RecursionIn the previous example,we defined a sqrt function,and now we can use it without remembering or caring about the details of how it is implemented.We sometimes say that we can treat it as a black box,meaning that it is unnecessary to look inside it to use it.This is crucial for maintaining sanity when building complex pieces of software.An even more interesting case is when we can think of the procedure that we’re in the middle of defining as a black box.That’s what we do when we write a recursive procedure.Recursive procedures are ways of doing a lot of work.The amount of work to be done is controlled by one or more arguments to the procedure.The way we are going to do a lot of work is by calling the procedure,over and over again,from inside itself!The way we make sure this process actually terminates is by being sure that the argument that controls how much work we do gets smaller every time we call the procedure again.The argument might be a number that counts down to zero,or a string or list that gets shorter.There are two parts to writing a recursive procedure:the base case(s)and the recursive case. The base case happens when the thing that’s controlling how much work you do has gotten to its smallest value;usually this is0or the empty string or list,but it can be anything,as long as you know it’s sure to happen.In the base case,you just compute the answer directly(no more calls to the recursive function!)and return it.Otherwise,you’re in the recursive case.In the recursive case, you try to be as lazy as possible,and foist most of the work offon another call to this function,but 1Hero of Alexandria is involved in this course in multiple ways.We’ll be studying feedback later on in the course, and Hero was the inventor of several devices that use feedback,including a self-filling wine goblet.Maybe we’ll assign that as afinal project...with one of its arguments getting smaller.Then,when you get the answer back from the recursive call,you do some additional work and return the result.Here’s an example recursive procedure that returns a string of n1’s:def bunchaOnes(n):if n==0:return""else:return bunchaOnes(n-1)+"1"The thing that’s getting smaller is n.In the base case,we just return the empty string.In the recursive case,we get someone else tofigure out the answer to the question of n-1ones,and then we just do a little additional work(adding one more"1"to the end of the string)and return it. Here’s another example.It’s kind of a crazy way to do multiplication,but logicians love it.def mult(a,b):if a==0:return0else:return b+mult(a-1,b)Trace through an example of what happens when you call mult(3,1),by adding a print statement as thefirst line of the function that prints out its arguments,and seeing what happens.Here’s a more interesting example of recursion.Imagine we wanted to compute the binary repre-sentation of an integer.For example,the binary representation of145is’10010001’.Our procedure will take an integer as input,and return a string of1’s and0’s.def bin(n):if n==0:return’0’elif n==1:return’1’else:return bin(n/2)+bin(n%2)The easy cases(base cases)are when we’re down to a1or a0,in which case the answer is obvious. If we don’t have an easy case,we divide up our problem into two that are easier.So,if we convert n/2into a string of digits,we’ll have all but the last digit.And n%2is1or0depending on whether the number is even or odd,so one more call of bin will return a string of’0’or’1’.The other thing that’s important to remember is that the+operation here is being used for string concatenation, not addition of numbers.How do we know that this procedure is going to terminate?We know that the number it’s operating on is getting smaller and smaller,and will eventually be either a1or a0,which can be handled by the base case.You can also do recursion on lists.Here’s another way to do our old favorite addList:def addList6(list):if list==[]:return0else:return list[0]+addList6(list[1:])There’s a new bit of syntax here:list[1:]gives all but thefirst element of list.Go read the section in the Python documentation on subscripts to see how to do more things with list subscripts. The addList procedure consumed a list and produced a number.The incrementElements1pro-cedure below shows how to use recursion to do something to every element of a list and make a new list containing the results.def incrementElements1(elts):if elts==[]:return[]else:return[elts[0]+1]+incrementElements1(elts[1:])Higher-order functionsWe’ve been talking about the fundamental principles of software engineering as being modularity and abstraction.But another important principle is laziness!Don’t ever do twice what you could do only once.2This standardly means writing a procedure whenever you are going to do the same computation more than once.In this section,we’ll explore ways of using procedures to capture common patterns in ways that might be new to you.What if wefind that we’re often wanting to perform the same procedure twice on an argument? That is,we seem to keep writing square(square(x)).If it were always the same procedure we were applying twice,we could just write a new functiondef squaretwice(x):return square(square(x))But what if it’s different functions?The usual strategies for abstraction seem like they won’t work. In the functional programming style,we treat functions asfirst-class objects.So,for example,we can do:>>>m=square>>>m(7)49And so we can write a procedure that consumes a function as an argument.So,now we could write:2Okay,so the main reason behind this rule isn’t laziness.It’s that if you write the same thing more than once,it will make it harder to write,read,debug,and modify your code reliably.def doTwice(f,x):return f(f(x))This is cool,because we can apply it to any function and argument.So,if we wanted to square twice,we could do:>>>doTwice(square,2)16Another way to do this is:def doTwiceMaker(f):return lambda x:f(f(x))This is a procedure that returns a procedure!The expression lambda y:y+y returns a function of a single variable;in this case that function returns a value that doubles its argument.For reasons that defy explanation,in Python,lambda doesn’t require a return expression,and it can only be used with a single expression;you can’t have if or for inside a lambda expression.If you need to put those in a function that you’re going to return,you have to name that function explicitly.So,for example,you could write it this way:def doTwiceMaker(f):def twoF(x):return f(f(x))return twoFNow,to use doTwiceMaker,we could do:>>>twoSquare=doTwiceMaker(square)>>>twoSquare(2)16>>>doTwiceMaker(square)(2)16A somewhat deeper example of capturing common patterns is sums.Mathematicians have invented a notation for writing sums of series,such as100i=1i or100i=1i2.Here’s one that gives us a way to computeπ:π2/8=100i=1,3,5,...1i2.It would be easy enough to write a procedure to compute any one of them.But even better is to write a higher-order procedure that allows us to compute any of them,simply:def sum(low,high,f,next):s=0x=lowwhile x<high:s=s+f(x)x=next(x)return sThis procedure takes integers specifying the lower and upper bounds of the index of the sum,the function of the index that is supposed to be added up,and a function that computes the next value of the index from the previous one.This last feature actually makes this notation more expressive than the usual mathematical notation,because you can specify any function you’d like for incrementing the index.Now,given that definition for sum,we can do all the special cases we described in mathematical notatation above:def sumint(low,high):return sum(low,high,lambda x:x,lambda x:x+1)def sumsquares(low,high):return sum(low,high,lambda x:x**2,lambda x:x+1)def piSum(low,high):return sum(low,high,lambda x:1.0/x**2,lambda x:x+2)>>>(8*piSum(1,1000000))**0.53.1415920169700393Now,we can use this to build an even cooler higher-order procedure.You’ve seen the idea of approximating an integral using a sum.We can express it easily in Python,using our sum higher-order function,asdef integral(f,a,b):dx=0.0001return dx*sum(a,b,f,lambda(x):x+dx)>>>integral(lambda x:x**3,0,1)0.2500500024999337We’ll do one more example of a very powerful higher-order procedure.Early in this chapter,we saw an iterative procedure for computing square roots.We can see that as a special case of a more general process of computing thefixed-point of a function.Thefixed point of a function f,called f∗,is defined as the value such that f∗=f(f∗).Fixed points can be computed by starting at an initial value x,and iteratively applying f:f∗=f(f(f(f(f(...f(x)))))).A function may have manyfixed points,and which one you’ll get may depend on the x you start with.We can capture this idea in Python with:def closeEnough(g1,g2):return abs(g1-g2)<.0001def fixedPoint(f,guess):next=f(guess)while not closeEnough(guess,next):guess=nextnext=f(next)return nextAnd now,we can use this to write the square root procedure much more compactly:def sqrt(x):return fixedPoint(lambda g:average(g,x/g),1.0)Another way to think of square roots is that to compute the square root of x,we need tofind the y that solves the equationx=y2,or,equivalently,y2−x=0.We can try to solve this equation using Newton’s method forfinding roots,which is another instance of afixed-point computation.3In order tofind a solution to the equation f(x)=0,we canfind a fixed point of a different function,g,whereg(x)=x−f(x)Df(x).Thefirst step toward turning this into Python code is to write a procedure for computing derivatives. We’ll do it by approximation here,though there are algorithms that can compute the derivative of a function analytically,for some kinds of functions(that is,they know things like that the derivative of x3is3x2.)dx=1.e-4def deriv(f):return lambda x:(f(x+dx)-f(x))/dx>>>deriv(square)<function<lambda>at0x00B96AB0>>>>deriv(square)(10)20.000099999890608Now,we can describe Newton’s method as an instance of our fixedPoint higher-order procedure. def newtonsMethod(f,firstGuess):return fixedPoint(lambda x:x-f(x)/deriv(f)(x),firstGuess) 3Actually,this is Raphson’s improvement on Newton’s method,so it’s often called the Newton-Raphson method.How do we know it is going to terminate?The answer is,that we don’t really.There are theorems that state that if the derivative is continuous at the root and if you start with an initial guess that’s close enough,then it will converge to the root,guaranteeing that eventually the guess will be close enough to the desired value.To guard against runawayfixed point calculations,we might put in a maximum number of iterations:def fixedPoint(f,guess,maxIterations=200):next=f(guess)count=0while not closeEnough(guess,next)and count<maxIterations:guess=nextnext=f(next)count=count+1if count==0:print"fixedPoint terminated without desired convergence"return nextThe maxIterations=200is a handy thing in Python:an optional argument.If you supply a third value when you call this procedure,it will be used as the value of maxIterations;otherwise, 200will be used.Now,having defined fixedPoint as a black box and used it to define newtonsMethod,we can use newtonsMethod as a black box and use it to define sqrt:def sqrt(x):return newtonsMethod(lambda y:y**2-x,1.0)So,now,we’ve shown you two different ways to compute square root as an iterative process:directly as afixed point,and indirectly using Newton’s method as a solution to an equation.Is one of these methods better?Not necessarily.They’re roughly equivalent in terms of computational efficiency. But we’ve articulated the ideas in very general terms,which means we’ll be able to re-use them in the future.We’re thinking more efficiently.We’re thinking about these computations in terms of more and more general methods,and we’re expressing these general methods themselves as procedures in our computer language.We’re capturing common patterns as things that we can manipulate and name.The importance of this is that if you can name something,it becomes an idea you can use. You have power over it.You will often hear that there are any ways to compute the same thing. That’s true,but we are emphasizing a different point:There are many ways of expressing the same computation.It’s the ability to choose the appropriate mode of expression that distinguishes the master programmer from the novice.MapWhat if,instead of adding1to every element of a list,you wanted to divide it by2?You could write a special-purpose procedure:def halveElements(list):if list==[]:return[]else:return[list[0]/2.0]+halveElements(list[1:])First,you might wonder why we divided by2.0rather than2.The answer is that Python,by default,given two integers does integer division.So1/2is equal to0.Watch out for this,and if you don’t want integer division,make sure that you divide by afloat.So,back to the main topic:halveElements works justfine,but it’s really only a tiny variation on incrementElements1.We’d rather be lazy,and apply the principles of modularity and abstraction so we don’t have to do the work more than once.So,instead,we write a generic procedure,called map,that will take a procedure as an argument,apply it to every element of a list,and return a list made up of the results of each application of the procedure.def map(func,list):if list==[]:return[]else:return[func(list[0])]+map(func,list[1:])Now,we can use it to define halveElements:def halveElements(list):return map(lambda x:x/2.0,list)Is this better than the previous methods?Yes,if youfind it clearer or more likely to get right. Otherwise,no.List ComprehensionsPython has a very nice built-in facility for doing many of the things you can do with map,called list comprehensions.The general template is[expr for var in list]where var is a single variable,list is an expression that results in a list,and expr is an expression that uses the variable var.The result is a list,of the same length as list,which is obtained by successively letting var take values from list,and then evaluating expr,and collecting the results into a list.Whew.It’s probably easier to understand it by example.>>>[x/2.0for x in[4,5,6]][2.0,2.5,3.0]>>>[y**2+3for y in[1,10,1000]][4,103,1000003]>>>[a[0]for a in[[’Hal’,’Abelson’],[’Jacob’,’White’],\[’Leslie’,’Kaelbling’]]][’Hal’,’Jacob’,’Leslie’]>>>[a[0]+’!’for a in[[’Hal’,’Abelson’],[’Jacob’,’White’],\[’Leslie’,’Kaelbling’]]][’Hal!’,’Jacob!’,’Leslie!’]>>>[div2(x)for x in[4,5,6]][2.0,2.5,3.0]ReduceAnother cool thing you can do with higher-order programming is to use the reduce function. Reduce takes a binary function and a list,and returns a single value,which is obtained by repeatedly applying the binary function to pairs of elements in the list.So,if the list contains elements x1...x n, and the function is f,the result will be f(...,f(f(x1,x2),x3),...,x n).This would let us write another version of addList:def addList7(list):return reduce(add,list)You can also use reduce to concatenate a list of lists.Remembering that the addition operation on two lists concatenates them,we have this possibly suprising result:>>>reduce(add,[[1,2,3],[4,5],[6],[]])[1,2,3,4,5,6]>>>addList7([[1,2,3],[4,5],[6],[]])[1,2,3,4,5,6]。
卡尔顿 SYSC 专业参考
Systems and Computer Engineering (SYSC)Systems and Computer Engineering (SYSC) CoursesSystems and Computer Eng.Faculty of Engineering & DesignNote: the Departments of Systems and Computer Engineering and Electronics offer courses in: Biomedical and Electrical Engineering, Communications Engineering, Computer Systems Engineering, Electrical Engineering, Software Engineering and Engineering Physics.SYSC 1005 [0.5 credit]Introduction to Software DevelopmentA first course in software development as an engineering discipline, using a modern programming language, Language syntax. Algorithm design. Tracing and visualizing program execution. Testing and debugging. Program style, documentation, reliability. Lab projects are drawn from a variety of application domains, for example, digital image manipulation; computer games; and robotics. Precludes additional credit for ECOR 1606 and SYSC 1101.Lectures two hours a week, tutorial one hour a week, laboratory three hours a week.SYSC 2001 [0.5 credit]Computer Systems FoundationsComputer architecture and organization: CPU, cache, memory, input/output, bus structures, interrupts; computer arithmetic: integer and floating point; CPU: instruction sets, addressing modes, instruction encoding. Input/output: programmed, interrupt-driven, block-oriented. Examples from several modern processor families.Prerequisite(s): ECOR 1606 or SYSC 1102 or SYSC 1005. Additional recommended background: SYSC 2006. Lectures three hours a week, laboratory two hours a week. SYSC 2002 [0.5 credit]Data Structures and AlgorithmsIn-depth experience in the design and constructionof computer programs involving data structures and different programming paradigms. Data structures, formal specification, abstract data types, graphs, recursion, finite state machines and object-oriented programming. Precludes additional credit for SYSC 2100 and SYSC 3002.Prerequisite(s): ECOR 1606.Lectures three hours a week, laboratory two hours a week.SYSC 2003 [0.5 credit]Introductory Real-Time SystemsPrinciples of event-driven systems. Review of computer organization. Assemblers and linkers. Developmentof embedded applications. Programming external interfaces, programmable timer. Input/output methods: polling, interrupts. Real-time issues: concurrency, mutual exclusion, buffering. Introduction to concurrent processes. Precludes additional credit for SYSC 3003 and SYSC 3006.Prerequisite(s): SYSC 2001 and (SYSC 2002 or SYSC 2006).Lectures three hours a week, laboratory two hours a week. SYSC 2004 [0.5 credit]Object-Oriented Software DevelopmentDesigning and implementing small-scale programs as communities of collaborating objects, using a dynamically-typed or statically-typed programming language. Fundamental concepts: classes, objects, encapsulation, information hiding, inheritance, polymorphism. Iterative, incremental development and test-driven development. Precludes additional credit for SYSC 1101.Prerequisite(s): SYSC 2002 or SYSC 2006 or permission of the department.Lectures three hours a week, laboratory two hours a week. SYSC 2006 [0.5 credit]Foundations of Imperative ProgrammingModular programming with a procedural language. Compilation and linking, libraries. Memory management and object lifetimes: static allocation, automatic allocation in stack frames, dynamic allocation from the heap. Introduction to data structures: dynamic arrays, linked lists. Collections: lists, stacks, queues. Introduction to recursion. Precludes additional credit for SYSC 1102 and SYSC 2002.Prerequisite(s): ECOR 1606 or SYSC 1005.Lectures three hours a week, laboratory two hours a week. SYSC 2100 [0.5 credit]Algorithms and Data StructuresThorough coverage of fundamental abstract collections: stacks, queues, lists, priority queues, dictionaries, sets, graphs. Data structures: review of arrays and linked lists; trees, heaps, hash tables. Specification, design, implementation of collections, complexity analysis of operations. Sorting algorithms.Precludes additional credit for SYSC 2002. Prerequisite(s): (SYSC 1102 or SYSC 2006) and (SYSC 1101 or SYSC 2004).Lectures three hours a week, laboratory two hours a week.SYSC 2101 [0.5 credit]Software Development ProjectDevelopment of expertise in designing, implementing, and testing industrial-quality, reusable code through individual and team projects. Applying and extending previously acquired knowledge of patterns, frameworks, UML, iterative and incremental development, Java and C+ + to medium- and large-scale systems.Prerequisite(s): SYSC 2100 or SYSC 2004.Lectures two hours a week, laboratory three hours a week. SYSC 3001 [0.5 credit]Operating Systems & DatabasesOperating systems and databases treated from a common perspective. Management of CPU, processes, memory, files, and data. Implications of concurrency. Concurrent programming, including interprocess communication in distributed systems. Data models and query languages. Precludes additional credit for SYSC 4001. Prerequisite(s): (SYSC 2002 or SYSC 2100), and SYSC 2003.Lectures three hours a week, laboratory/problem analysis two hours a week.SYSC 3006 [0.5 credit]Computer OrganizationComputer organization: processor, memory, input/ output, system bus. Number systems: binary, decimal, hexadecimal. Assembly language programming: representation of data, instruction encoding, execution. Devices: keyboard, programmable timer, parallel interface. Input/output methods: polling, hardware/software interrupts.Precludes additional credit for SYSC 2001 and SYSC 2003. May not be taken for credit by students in Computer Systems Engineering, Communications Engineering, or Software Engineering.Prerequisite(s): (SYSC 2002 or SYSC 2006) and ELEC 2607.Lectures three hours a week, laboratory two hours a week. SYSC 3010 [0.5 credit]Computer Systems Development Project Development of expertise in designing, implementingand testing maintainable, reusable software through team projects. Applying modern programming languages, design patterns, frameworks, UML and modern development processes (refactoring, iterative and incremental development, version control techniques) to medium-scale projects; for example, embedded or mobile applications.Precludes additional credit for SYSC 2101 and SYSC 3110.Prerequisite(s): SYSC 2004 and SYSC 2100, and third-year status in Computer Systems Engineering.Lectures two hours a week, laboratory three hours a week.SYSC 3020 [0.5 credit]Introduction to Software EngineeringIntroduction to software engineering principles,software development life-cycles. Modelling in software engineering. Current techniques, notations, methods, processes and tools used in software engineering. UML modelling. Introduction to software quality, software verification and validation, software testing.Precludes additional credit for SYSC 3120 and SYSC 4120.Prerequisite(s): SYSC 2004 and SYSC 2006.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 3100 [0.5 credit]Systems Analysis and DesignCreating requirements specifications prior to designing and implementing complex software systems. Software development lifecycles, role of requirements analysis; functional decomposition, dataflow modeling; database modeling, entity-relationship diagrams; finite state machines; object-oriented analysis; use cases, use case maps; project management; introduction to software design.Precludes additional credit for BUSI 3402.Prerequisite(s): SYSC 2004 or SYSC 2100.Lectures three hours a week, laboratory/problem analysis two hours a week.SYSC 3101 [0.5 credit]Programming LanguagesPrinciples underlying different kinds of programming languages (procedural, functional, logic programming) and their semantics. Overview of machinery needed for language support (compilers, interpreters and run-time systems).Prerequisite(s): SYSC 2004 or SYSC 2100.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 3110 [0.5 credit]Software Development ProjectDevelopment of expertise in designing, implementingand testing maintainable, reusable software through team projects. Applying modern programming languages, design patterns, frameworks, UML and modern development processes (detection of olfactible source code defects, refactoring, iterative and incremental development, version control techniques) to medium-scale projects.Precludes additional credit for SYSC 2101 and SYSC 3010.Prerequisite(s): SYSC 2004 and SYSC 2100, and third-year status in Software Engineering.Lectures two hours a week, laboratory three hours a week.SYSC 3120 [0.5 credit]Software Requirements EngineeringCurrent techniques, notations, methods, processes and tools used in Requirements Engineering. Requirements elicitation, negotiation, modelling requirements, management, validation. Skills needed for Requirements Engineering and the many disciplines on which it draws. Requirements analysis: domain modelling, modelling object interactions; UML modelling. Introduction to software development processes.Precludes additional credit for SYSC 3020. Prerequisite(s): SYSC 2004 and SYSC 2100 and third-year status in Software Engineering.Lectures three hours a week, laboratory two hours a week. SYSC 3200 [0.5 credit]Industrial EngineeringTechniques of operations research for decision-makingin complex engineering systems. Linear programming, network models, PERT, integer programming, dynamic programming, queuing systems and inventory models. Problem solving is emphasized.Precludes additional credit for BUSI 2300, ECON 4004, or MATH 3801.Prerequisite(s): MATH 1004 and MATH 1104 and (ECOR 1606 or SYSC 1100).Lectures three hours a week, laboratory/problem analysis 1.5 hours per week.SYSC 3303 [0.5 credit]Real-Time Concurrent SystemsPrinciples and practice of a systems engineering approach to the development of software for real-time, concurrent, distributed systems. Designing to achieve concurrency, performance, and robustness, using visual notations. Converting designs into programs. Introduction to hard real-time systems. Team project.Prerequisite(s): for students in the Faculty of Engineering and Design, SYSC 2003 and (SYSC 2004 or SYSC 2100); for students in Computer Science, (COMP 2003 or COMP 2401) and (COMP 2002 or COMP 2402).Lectures three hours a week, laboratory two hours a week. SYSC 3500 [0.5 credit]Signals and SystemsSignals: energy and power signals, discrete-time and continuous. Linear systems and convolution. Fourier Transform; complex Fourier series; signal spectral properties and bandwidth. Laplace transform and transient analysis. Transfer functions, block diagrams. Baseband and passband signals, with applications to communications systems.Precludes additional credit for SYSC 3600 and SYSC 2500.Prerequisite(s): MATH 2004.Lectures three hours a week, problem analysis three hours alternate weeks.SYSC 3501 [0.5 credit]Communication TheoryReview of signals, linear systems and Fourier theory; signal bandwidth and spectra; digital waveform coding; introduction to analog and digital modulation systems; synchronization; characterization and effects of noise; link budgets; communications media and circuits; applications to current communications systems.Precludes additional credit for SYSC 3503. Prerequisite(s): MATH 3705 and SYSC 3600.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 3503 [0.5 credit]Communication Theory IIAmplitude Modulation. Frequency Modulation. Performance of AM and FM in noise. Communication channels, channel models, noise sources, noise models. Digital modulation: ASK, FSK, PSK. Optimal reception, probability of error on the AWGN channel.Precludes additional credit for SYSC 3501 or SYSC 4600. Prerequisite(s): (SYSC 2500 or SYSC 3500) and STAT 2605.Lectures three hours a week, laboratory, three hours alternate weeks.SYSC 3600 [0.5 credit]Systems and SimulationProperties of linear systems. Linear dynamic modelsof engineering systems. Applications of the Laplace transform. Transfer functions. Block diagrams. Frequency and time response. System simulation with digital computers.Precludes additional credit for SYSC 2500 or SYSC 3500. Prerequisite(s): MATH 1005, and (ECOR 1101 or PHYS 1001).Lectures three hours a week, laboratory three hours a week.SYSC 3601 [0.5 credit]Microprocessor SystemsMicroprocessor-based system design for different microprocessor families. Microprocessors: internal organization, instruction sets, address generation, pin-outs, bus cycles, signalling waveforms. Interfacing memory and I/O devices. Interrupt structures, direct memory access. Floating point coprocessors. System bus standards. Introduction to DSPs.Precludes additional credit for ELEC 4601. Prerequisite(s): ELEC 2607, and SYSC 2003 or permission of the department.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 3999 [0.0 credit]Co-operative Work TermSYSC 4001 [0.5 credit]Operating SystemsIntroduction to operating system principles. Processes and threads. CPU scheduling. Managing concurrency: mutual exclusion and synchronization, deadlock and starvation. Managing memory and input/output. Concurrent programming, including interprocess communication in distributed systems.Precludes additional credit for SYSC 3001. Prerequisite(s): (SYSC 2002 or SYSC 2100) and (SYSC 2003 or SYSC 3006).Lectures three hours a week, laboratory /problem analysis two hours a week.SYSC 4005 [0.5 credit]Discrete Simulation/ModelingSimulation as a problem solving tool. Random variable generation, general discrete simulation procedure: event table and statistical gathering. Analyses of simulation data: point and interval estimation. Confidence intervals. Overview of modeling, simulation, and problem solving using SIMSCRIPT, MODSIM, and other languages. Prerequisite(s): (STAT 2605 or STAT 3502) andfourth-year status in Engineering, or permission of the Department.Also offered at the graduate level, with different requirements, as SYSC 5001, for which additional credit is precluded.Lectures three hours a week, laboratory one hour a week. SYSC 4101 [0.5 credit]Software ValidationTechniques for the systematic testing of software systems. Software validation and verification, software debugging, quality assurance, measurement and prediction of software reliability. Emphasis on the treatment of these topics in the context of real-time and distributed systems. Prerequisite(s): SYSC 3100 or SYSC 3120 or SYSC 3020. Lectures three hours a week, laboratory/problem analysis three hours alternate weeks.SYSC 4102 [0.5 credit]Performance EngineeringTechniques based on measurements and models, for predicting and evaluating the performance of computer systems. Instrumentation. Simple queueing modelsand approximations. Techniques for modifying software designs to improve performance.Prerequisite(s): STAT 3502, and (SYSC 3001 or SYSC 4001).Also offered at the graduate level, with different requirements, as SYSC 5101, for which additional credit is precluded.Lectures three hours a week, laboratory/problem analysis three hours alternate weeks.SYSC 4105 [0.5 credit]Engineering ManagementIntroduction to engineering management: management of new products, management of manufacturing processes, management of the linkages between new products and manufacturing processes. Current theories, concepts and techniques are stressed, using a combination of readings, cases and guest speakers.Prerequisite(s): fourth-year status in Engineering. Lectures three hours a week.SYSC 4106 [0.5 credit]Software Product ManagementStages of the life cycle of software products and their implications for architecture definition, requirements specification, variety, target market segmentation, adoption, roll-out plans, documentation, maintenance, skills, building prototypes, testing, feature prioritization, quality and tools infrastructures.Prerequisite(s): SYSC 3100 or SYSC 3020 or SYSC 3120 (SYSC 3020 and SYSC 3120 can be taken concurrently) or COMP 3004.Lectures three hours a week, laboratory/problem analysis two hours a week.SYSC 4107 [0.5 credit]Software BusinessEstablishing and growing businesses anchored on software design and development. Models for software business; partnerships with suppliers and customers; distribution; raising money; intellectual property protection; evolving core products and sources of competitive advantage; alignment among the business model, infrastructures, and software development. Prerequisite(s): fourth-year status in Engineering or Computer Science.Lectures three hours a week.SYSC 4120 [0.5 credit]Modelling Software DesignImportance of modelling software design. Software design in software engineering. Current techniques, notations, methods, processes and tools used in software design. Software system design, object design, design patterns; UML modelling. Quality assurance of designs. Modelling state-based behaviour.Precludes additional credit for SYSC 3020. Prerequisite(s): SYSC 3120.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4201 [0.5 credit]Ethics, Research Methods and Standards for Biomedical EngineeringEthical theories, ethical decision-making, codes; human and animal experimentation, consent, practices of ethical review boards; research methods and regulations for design, manufacture, certification of medical devices; data collection, management, analysis, including security, confidentiality, privacy; bioethical dilemmas, impact of technology and research (social, political, financial). Prerequisite(s): fourth-year status in Biomedical and Electrical Engineering or Biomedical and Mechanical Engineering.Lectures three hours a week, problem analysis three hours alternate weeks.SYSC 4202 [0.5 credit]Clinical EngineeringOverview of the Canadian health care system; brief examples of other countries; clinical engineering andthe management of technologies in industrializedand in developing countries; safety, reliability, quality assurance; introduction to biomedical sensor technologies; applications of telemedicine; impact of technology on health care.Prerequisite(s): fourth-year standing in Biomedical and Electrical or Biomedical and Mechanical Engineering, or fourth-year standing in Engineering and permission of the Department.Lectures three hours a week, problem analysis three hours alternate weeks.SYSC 4203 [0.5 credit]Bioinstrumentation and SignalsBioinstrumentation and biological signals; instrumentation systems, noise, and electrical safety; bioelectric signals; biomagnetic signals; measurement of flow and pressure; data acquisition; signal processing; biomedical imaging technologies; amplifier design for biosensors; major physiological systems and associated measurements. Prerequisite(s): (SYSC 3600 or SYSC 3500) and (ELEC 2507 or ELEC 3605) and fourth-year status in Biomedical and Electrical Engineering or fourth-year status in Biomedical and Mechanical Engineering.Lectures three hours a week, laboratory/problem analysis three hours alternate weeks.SYSC 4205 [0.5 credit]Image Processing for Medical ApplicationsTwo-dimensional signals, filters, and Fourier transforms. Image acquisition, sampling, quantization and representation. Image perception. Digital and film cameras. Medical imaging technologies. Image processing operations: histogram, convolution, morphological, segmentation, registration. Image compression and formats.Prerequisite(s): MATH 3705 and fourth-year status in Engineering.Lectures three hours a week, laboratory/problem analysis three hours alternate weeks.SYSC 4405 [0.5 credit]Digital Signal ProcessingDiscrete time signal and system representation: time domain, z-transform, frequency domain. Sampling theorem. Digital filters: design, response, implementation, computer-aided design. Spectral analysis: the discrete Fourier transform and the FFT. Applications of digital signal processing.Prerequisite(s): SYSC 2500 or SYSC 3500 or SYSC 3600. Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4502 [0.5 credit]Communications SoftwareLayered communication software models and Internet protocols. FSM, EFSM, and MSC. APIs and socket programming. Routing algorithms and data structures. Packet scheduling algorithms and real-time operating systems. Layer integration and implementation issues. Precludes additional credit for SYSC 3502. Prerequisite(s): SYSC 4602 and (SYSC 2004 or SYSC 2100), and fourth year status in Electrical Engineering, Computer Systems Engineering, or Software Engineering, or third year status in Communications Engineering. Lectures three hours a week, problem analysis three hours alternate weeks.SYSC 4504 [0.5 credit]Distributed Network ProcessingSoftware aspects of distributed networks. Client-server systems. Internet and the WWW. LAN’s and WAN’s, routing protocols. Transportable software, Java applets. Use of modern software tools in communication network monitoring and analysis. Network management. Prerequisite(s): SYSC 2004 or SYSC 2100. Additional recommended background: SYSC 4602 or SYSC 3303. Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4505 [0.5 credit]Automatic Control Systems IReview of Laplace transform techniques. Effects of feedback: frequency response, pole-zero positions. Compensation: root locus, Bode plots. State variables: formulation, solution of linear systems, examples of simple second-order non-linear systems. Discrete time systems: z-transforms. Signal reconstruction.Precludes additional credit for MAAE 4500. Prerequisite(s): MATH 2004 and (SYSC 2500 or SYSC 3500 or SYSC 3600).Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4507 [0.5 credit]Computer Systems ArchitectureHistory of computers: evolution of concepts, influence of technology, techniques to increase performance. Detailed analysis and design of ALUs, control units, memory systems. Multiprocessor systems, pipeline and array processing. Scalable, superscalar, RISC, CISC, fault tolerant, and digital signal processing architectures. Prerequisite(s): ELEC 2607 and (SYSC 2001 or SYSC 3006).Lectures three hours a week, laboratory/problem analysis one hour a week.SYSC 4600 [0.5 credit]Digital CommunicationsReview of probability, random variables, signal representation. Baseband data transmission: Nyquist criterion, equalization, optimal receiver, error probability. Digital modulation, performance. Synchronization. Introduction to information theory. Error detection and correction. Spread spectrum. Applications to current digital wired and wireless communications systems.Precludes additional credit for SYSC 3503 and SYSC 4604.Prerequisite(s): SYSC 3501 and STAT 3502.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4602 [0.5 credit]Computer CommunicationsLayered protocol architectures, OSI. Physical media, physical layer interfaces, data transmission. Data-link protocols, multiplexing, polling. LANs, IEEE 802 standards, performance. Switched Ethernets, FDDI, bridges. Wide area networks, packet-switching networks, X.25. Frame relay, internetworking, DoD protocols, TCP, UDP. ATM LANs, adaptation layers, traffic issues. Prerequisite(s): STAT 2605 or STAT 3502 (may be taken concurrently), and fourth-year status in Biomedical and Electrical, Electrical, Computer Systems, Software, or Sustainable and Renewable Energy Engineering, or third-year status in Communications Engineering.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4604 [0.5 credit]Digital Communication TheoryIntroduction to information theory, source coding and data compression, Error control coding, Trellis coded modulation, advanced topics of current interest: spread spectrum; digital wireless communications.Precludes additional credit for SYSC 4600. Prerequisite(s): SYSC 3503.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4607 [0.5 credit]Wireless CommunicationsWireless radio channel characterization, diversity, equalization; cellular architecture, multiple access principles, spread spectrum systems, radio resource management; examples from modern wireless systems, networks, and standards, including cellular networks, WLANs, ad hoc networks, and satellite systems. Prerequisite(s): SYSC 3501 or SYSC 3503.Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4700 [0.5 credit]Telecommunications Engineering Telecommunications as a national and international infrastructure. Systems view of network architecture: transmission, access, switching, multiplexing, signalling, and teletraffic. Network planning, management,security and control. Role of government, regulationand competition. Current telecommunications network evolution.Prerequisite(s): fourth-year status in Electrical, Computer Systems or Communications Engineering, and (SYSC 3501 or SYSC 3503).Lectures three hours a week, laboratory/problem analysis three hours alternate weeks.SYSC 4701 [0.5 credit]Communications Systems LabProject-oriented level experience in the design of communication systems to meet user requirements. Lectures on queuing theory and teletraffic analysis; system specification and design: requirements analysis, solution alternatives, evaluation of alternative technologies, design, costing, implementation, test.Prerequisite(s): fourth-year status in Communications Engineering.Lectures two hours a week, laboratory four hours a week. SYSC 4800 [0.5 credit]Software EngineeringReview of software lifecycles and requirements analysis. Software design, with emphasis on methods for real-time systems. Testing, verification and validation, quality assurance and control. Project planning and management. Maintenance and configuration management. Software reuse during design and maintenance.Prerequisite(s): SYSC 3001 and SYSC 3100 and SYSC 3303 (SYSC 3001 and SYSC 3303 may be taken concurrently).Lectures three hours a week, laboratory three hours alternate weeks.SYSC 4805 [0.5 credit]Computer Systems Design LabDeveloping professional-level expertise in selected, important areas of the field by applying, honing, integrating, and extending previously acquired knowledge in team projects in the laboratory. Lecture periods are devoted to new knowledge required for the selected areas, to project-related issues, and to student presentations. Prerequisite(s): SYSC 3303 and (SYSC 3020 or SYSC 4800) and fourth-year status in Computer Systems Engineering (students are encouraged to enrol in both SYSC 4800 AND 4805 in the same academic year). Lectures two hours a week, laboratory four hours a week. SYSC 4806 [0.5 credit]Software Engineering LabApplying the full spectrum of engineering and programming knowledge acquired in the program through team projects in the laboratory. Practice in doing presentations and reviews. Lectures will discuss software engineering issues as they relate to the projects, from a mature point of view.Prerequisite(s): SYSC 4800 or SYSC 4120 and fourth-year status in Software Engineering.Lectures two hours a week, laboratory four hours a week. SYSC 4906 [0.5 credit]Special TopicsAt the discretion of the Department, a course dealingwith selected advanced topics of interest to students in Biomedical and Electrical, Communications, Computer Systems, Electrical, Software Engineering, and Engineering Physics may be offered.Prerequisite(s): permission of the Department.SYSC 4907 [1.0 credit]Engineering ProjectStudent teams develop professional-level experienceby applying previously acquired knowledge to a major design project. Lectures discuss project-related issues and student presentations. A project proposal, interim report, oral presentations, and a comprehensive final report are required.Prerequisite(s): fourth-year status in Engineering and ECOR 4995 (may be taken concurrently). Certain projects may have additional prerequisites.Lecture one hour a week, laboratory seven hours a week. SYSC 4917 [1.0 credit]Biomedical Engineering ProjectStudent teams develop professional-level experienceby applying previously acquired knowledge to a major design project in biomedical engineering. Lectures discuss project-related issues and student presentations. A project proposal, interim report, oral presentations, and a comprehensive final report are required.Prerequisite(s): fourth-year standing in Biomedical and Electrical Engineering and ECOR 4995 (may be taken concurrently). Certain projects may have additional prerequisites.Lecture one hour a week, laboratory seven hours a week.SYSC 4927 [1.0 credit]Software Engineering ProjectStudent teams gain professional-level experience by applying and extending previously acquired knowledge in a major design project in software engineering. Lectures discuss project-related issues and student presentations.A project proposal, interim report, oral presentations, and a comprehensive final report are required.Prerequisite(s): fourth-year status in Software Engineering and ECOR 4995 (may be taken concurrently). Certain projects may have additional prerequisites.Lecture one hour a week, laboratory seven hours a week. SYSC 4937 [1.0 credit]Communications Engineering ProjectStudent teams gain professional-level experience by applying and extending previously acquired knowledgein a major design project in communications engineering. Lectures discuss project-related issues and student presentations. A project proposal, interim report, oral presentations, and a comprehensive final report are required.Prerequisite(s): fourth-year status in Communications Engineering and ECOR 4995 (may be taken concurrently). Certain projects may have additional prerequisites. Lecture one hour a week, laboratory seven hours a week. Summer session: some of the courses listed in this Calendar are offered during the summer. Hours and scheduling for summer session courses will differ significantly from those reported in the fall/winter Calendar. To determine the scheduling and hours for summer session classes, consult the class schedule at central.carleton.caNot all courses listed are offered in a given year. For an up-to-date statement of course offerings for the current session and to determine the term of offering, consult the class schedule at central.carleton.ca。
软件工程双语教学大纲
软件工程》（双语）教学大纲 课程编号：06301525 课程性质： 必修 课程名称：软件工程概论 学时 / 学分： 48/2.5 英文名称：Software Engineering 考核方式： -pT 、“、-IV. 《Software Engineering — Practitioner '选用教材： Approach 》 Fifth Edition, R.S.Pressman,Mc 大纲执笔人： 顾春华 Graw Hill ， 清华大学出版社影印先修课程：高级语言程序设计、数据库原理大纲审核人： 适用专业： 计算机科学与技术一、教学基本目标软件工程》是计算机科学与技术专业本科生的一门的专业基础课，旨在使学生掌握软件工程的基本概念、 原理和方法， 从软件开发技术、 软件工程管理和软件工程环境等几个方面了解如何将系统的、 规范化的和可以度量的工程方法运用于软件开发和维护中。
要求学生通过本门课的学习，掌握结构化方法、面向对象方法等软件开发技术，初步了解软件复 用的概念及基于构件的开发方法，同时对软件工程管理和环境等内容有一个总体的了解。
二、教学基本内容 第一章 绪论（ Introduction ） 本章主要介绍软件的基本概念、软件危机、软件工程学的范畴、传统软件工程和面向对象软 件工程以及软件工程的应用。
重点掌握：学习软件工程的意义， （Software Lifecycle and Software Development Model ） 介绍了传统的软件开发模型 （瀑布模型、 快速原型模型） 、软 、面向对象过程模型（构件集成模型） 、基于形式化方法的软 重点掌握：各种软件开发模型的内容，不同开发模型的特点比较。
第三章 软件需求分析 （Software Requirement Analysis ） 需求分析是软件生存周期中的一个重要阶段，本章在介绍了软件需求分析的任务、步骤后， 分别按结构化和面向对象两类方法，给出了需求分析模型和它们的描述工具，并结合实例进一步 阐述了结构化分析和面向对象分析的过程。
CH08 Software Prototyping 软件工程讲义英语版 教学课件
©Ian Sommerville 2000
Software Engineering, 6th edition. Chapter 8
Slide 11
Approaches to prototyping
Establish prototype objectives
Prototyping plan
Define prototype functionality
The objective of throw-away prototyping is to validate or derive the system requirements. The prototyping process starts with those requirements which are poorly understood
A working system is available early in the process
The prototype may serve as a basiscation
The system can support user training and system testing
Based on techniques which allow rapid system iterations
Verification is impossible as there is no specification. Validation means demonstrating the adequacy of the system
Develop prototype
Prototyping plan
Outline definition
Executable prototype
《IT职业英语教程》二级软件各章文档重点句子翻译
《IT职业英语教程》二级软件各章文档重点句子翻译总结此可行性研究报告意在为行星跟踪软件寻找可行的设计方案。
可行性研究报告是由通用电脑公司的101团队于2005年6月15日至2005年6月21日内编制。
This document is a report on the feasibility study conducted on the proposedsolutions for the Planet Tracking Software. The feasibility study was conducted between June15th, 2005 and June 21st, 2005 by Group 101, GCC Corporation.实施可行性研究考查的是软件如何变换风险承担者和用户的角色，以及新的工作流程和组织结构能否被用户和风险承担者所接受。
An operational feasibility study examines how the software will change theroles of the stakeholders and the users and whether the new workflow andorganizational structure will be accepted by the users and stakeholders技术可行性研究考查的是在现有团队和环境的技术条件下，将用于行星跟踪软件中的提议的设计方案是否可行。
A technical feasibility study checks to see if the proposed solution is feasiblegiven the skills of our group and the environment the software is expected to bedeployed in the Planet Tracking Software.时间可行性研究考查提议的设计方案能否在某种意义上确保满足宇宙工程公司要求的和其他客户要求的最终期限。
【大学课件】Software Engineering软体工程(英文课件)
Symptom of Software Crisis
About US$250 billions spent per year in the US on application development
Out of this, about US$140 billions wasted due to the projects getting abandoned or reworked; this in turn because of not following best practices and standards
ppt课件
4
Contents
Software Crisis Software Myths What is Software Engineering Evolution of Software Engineering State-of-art in Software Engineering
Software Engineering 軟體工程
ppt课件
1
Course Obout all the difficulties in developing software so that we can avoid pitfalls and myths in software design
average time
overrun = 222%.
53%
Project completion
61% of originally specified features included
16%
✓
?
On time, on budget, with all of the specified features and functions
软件工程专业的核心课程
软件工程专业通常包含一系列核心课程，这些课程旨在为学生提供深厚的计算机科学和软件工程知识，培养其在软件开发和工程实践中的技能。
以下是软件工程专业的一些核心课程：1. 计算机科学导论（Introduction to Computer Science）： 介绍计算机科学的基本概念、算法和编程技术。
2. 离散数学 （Discrete Mathematics）： 提供数学基础，特别是对于在算法设计和分析中起关键作用的离散结构的理解。
3. 数据结构与算法（Data Structures and Algorithms）： 学习常见数据结构（如树、图、队列、栈等）和算法设计与分析。
4. 数据库系统 （Database Systems）： 掌握数据库设计、管理和查询语言，了解数据库系统的原理和实践。
5. 操作系统 （Operating Systems）： 理解操作系统的基本原理，包括进程管理、内存管理、文件系统等。
6. 软件工程导论（Introduction to Software Engineering）： 介绍软件工程的基本概念、原理和方法，包括软件开发生命周期、需求分析、设计、测试等。
7. 软件项目管理（Software Project Management）： 学习项目管理的基本原理和技能，特别是在软件开发项目中的应用。
8. 计算机网络（Computer Networks）： 理解计算机网络的基本原理、协议和技术，包括网络通信、传输层协议等。
9. 人机交互 （Human-Computer Interaction）： 学习设计用户友好的软件界面和用户体验，了解人机交互的基本原理。
10. 软件测试与质量保障（Software Testing and Quality Assurance）： 学习软件测试的方法、工具和策略，以确保软件质量。
11. 编程语言原理（Principles of Programming Languages）： 理解不同编程语言的设计原理和语法结构。
12_Introduction_to_Software_Architecture
12 软件体系结构概述
12.1.1 什么是“体系结构”
词典的定义：
The art and science of designing and erecting buildings (建 筑学：设计和建造建筑物的艺术与科学)； A style and method of design and construction (设计及构造 的方式和方法)； Orderly arrangement of parts; structure (部件的有序安排；结 构)； The overall design or structure of a computer system, including the hardware and the software required to run it, especially the internal structure of the microprocessor (计算 机系统的总体设计或结构，包括其硬件和支持硬件运行的软 件，尤其是微处理器内部的结构)。
12 软件体系结构概述
起源于建筑学的“体系结构”
“体系结构(Architecture)”一词起源于建筑学
如何使用基本的建筑模块构造一座完整的建筑？
包含两个因素：
基本的建筑模块：砖、瓦、灰、沙、石、预制梁、柱、屋面 板… 建筑模块之间的粘接关系：如何把这些“砖、瓦、灰、沙、石、 预制梁、柱、屋面板”有机的组合起来形成整体建筑？
连接发生和维持的机制——实现连接的物质基础(连接的机 制)； 连接能够正确、无二义、无冲突进行的保证——连接正确有 效的进行信息交换的规则(连接的协议)。 简称“机制”(mechanism)和“协议”(protocol)。
12 软件体系结构概述
连接的机制(Mechanism)
An Introduction to Software Engineering(o)
Slide 3
Software engiies of ALL developed nations are dependent on software. More and more systems are software controlled Software engineering is concerned with theories, methods and tools for professional software development. Expenditure on software represents a significant fraction of GNP in all developed countries.
Software Engineering, 8th edition. Chapter 1 Slide 5
FAQs about software engineering
What is software? What is software engineering? What is the difference between software engineering and computer science? What is the difference between software engineering and system engineering? What is a software process? What is a software process model?
Software Engineering, 8th edition. Chapter 1
Slide 2
Topics covered
软件工程基础教程(英文版)
2. Service-oriented
3. Globalization (English)
·强调开放性、交互性 ·支持主流的开放式标准 ·人才的全球化
Q:对中国软件业有什么启示和挑战？
About this course (2)
教材: <<An Basic Introduction to Software Engineering >>,2012.1.
17
Lecture Schedule (temp 2)
周次/Week 课题/Topic 作业/Assignments Due
10
MidReview
11
Project Management
Chap8 , HW#8
12
Risk Management
Chap9
13
Quality Assurance
Chap10
14 15 16
Tools and Methods Advanced topics Final Review
Chap11 (可能提前介绍)
Project Demo, Paper and Documents
18
Some Good and Bad Examples
以前同学的表现， “好的表现都比较相似，不好的各有 各的不同（的表现）。”
Requirements Engineering
Design Engineering Code Testing Techniques Testing Strategies Maintenace Midterm
Chap 3, HW#3
Chap4, HW#4 Chap5, HW#5 Chap6 ,HW#6 Chap7, HW#7 Chap8 Midterm Project Demo and In-Class exam
Lecture 2_Introduction to Software Architecture
Hardest to change Most critical to get right
Communicate back to Customer Avoid problems during integration Testing Planning Assess risks and budgets.
Architecting a dog house
Can be developed or build by one person as it requires:• Minimal modeling • Simple Process • Simple tools
Architecting a house
Software Architecture (Continuous)
Poorly defined or ill defined architecture makes it nearly impossible to meet the product requirements. Without proper planning in the architecture design stages, software production may be very inefficient in terms of time and cost.
An average software project: - 5-10 people - 10-15 month duration - 3-5 external interfaces - Some unknowns & risks Defense Weapon System National Air Traffic Control System
软件设计英语作文
软件设计英语作文Software Design: An English CompositionIn the realm of software development, design serves as the blueprint for creating efficient, scalable, and user-friendly applications. A well-thought-out software design ensures that the final product meets the desired requirements and exceeds user expectations. This essay aims to explore the key aspects of software design and its significance in the development process.1. Introduction to Software DesignSoftware design is an integral part of the software development lifecycle. It involves transforming user requirements into a detailed plan that outlines the structure, components, and behavior of the software. A robust design serves as a roadmap for developers, guiding them through the coding, implementation, and testing phases.2. Importance of Software Designa. Meeting User Needs: A well-designed software application addresses the specific requirements and expectations of its intended users. By thoroughly understanding user needs, developers can create a solution that is both functional and intuitive.b. Scalability: Good design allows software to adapt and grow as requirements change over time. This ensures that the application can handle increased workload, new features, and evolving technologieswithout significant rework.c. Maintainability: A well-structured design makes it easier to maintain and update the software. This results in reduced downtime, lower costs, and improved user satisfaction.d. Reusability: A well-designed software component can be reused in other projects, saving time and effort in the development process. This promotes a modular approach to software design, fostering code reusability and reducing redundancy.3. Key Aspects of Software Designa. Architecture: The software architecture defines the overall structure of the application, including its components, relationships, and interactions. A solid architecture ensures that the software is robust, secure, and efficient.b. Data Design: This aspect focuses on organizing and structuring the data within the application. Effective data design leads to optimized database performance, data integrity, and ease of data manipulation.c. Interface Design: The interface design determines how users interact with the software. A user-friendly interface enhances the overall user experience, making the application more accessible and intuitive.d. Component Design: This involves designing individual software components, such as classes, modules, and functions. Well-designed components are modular, maintainable, and reusable.4. ConclusionIn conclusion, software design plays a pivotal role in the development process. It ensures that the final product meets user needs, is scalable, maintainable, and reusable. By focusing on key aspects like architecture, data design, interface design, and component design, developers can create software that stands the test of time and delivers an exceptional user experience.。
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What is Software?
Software is: Computer programs and associated documentation Instructions (Computer programs) that when executed provide desired features, function, and performance. The are basically two kinds of software products:
Software specification Software development Software validation Software evolution
Software Process Activities
Software Specification In software specification, the customers and the engineers usually describes, what the system should do and its development constraints.
Kind of Software Products
Generic products (Continuous) Examples of such products are software for PCs such as:
Databases, word processors, drawing packages, project management tools etc.
40
Software Evolution Changing the software in response to changing demands.
Cost of Software Engineerinof costs are development costs, 40% are testing costs. For custom software, evolution costs often exceed development costs. Costs of the software system usually vary depending upon the type of system being produced and the requirements of system attributes such as performance and system reliability.
FAQs about Software Engineering
What is software? What is software engineering? What is a software process? What is a software process model?
FAQs about Software Engineering
What are the costs of software engineering? What is CASE (Computer-Aided Software Engineering) What are the attributes of good software? What are the important challenges facing software engineering?
What is Software Engineering?
It is an engineering discipline which is concerned with all aspects of software production. Software engineers should adopt a systematic and organized approach to their work and use appropriate tools and techniques depending on the problem to be solved, the development constraints and the resource available.
Software Validation Checking that the software is what the customer wants or checking the software against the customer requirements.
Software Process Activities
Software Process Activities
Software Development Production of the software system i.e. where software is designed and programmed.
Software Process Activities
Generic Products Bespoke or customized products.
Kind of Software Products
Generic products Developed to be sold to a range of different customers. This category of software products is bond to multiple users in the market. The requirements of these software products are usually elicited either by the competitor products or through market surveys. Sometimes developing the innovating requirements also plays an important role for the success of the software product.
Software Cost Software cost often dominate system costs. The costs of software on a PC are often greater than the hardware cost. Software costs more to maintain then it does to develop. For systems with a long life, maintenance costs may be several times development costs. Software engineering is mainly concerned with cost effective software development.
In today’s world, individuals and society highly rely on effective software systems. There is a need to develop reliable and trustworthy software systems within time and budget.
Software Engineering
Software engineering is mainly concerned with theories, methods and tools for professional software development. Software engineering is defined as :
“ The application of a systematic, disciplined, quantifiable approach to the development, operation, and maintenance of software.”
Software Engineering
Software Engineering
In today’s world, the economies of all developed nations are dependent on software. More and more systems are software controlled.
Introduction to Software Engineering
Usman Farooq sf_usman@
Goal(s) of this lecture
To introduce software engineering and its importance. To introduce different software engineering techniques for different kinds of software systems. To introduce Software Process.
Kind of Software Products
Bespoke Products Develop for a single customer according to their specification. Software products are designed according to the requirements of a customer.
What is a Software Process?
A set of activities whose aim/goal is the development or evolution of software. There are four important activities that are common to all software processes: