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Out of these cookies, the cookies that are categorized as necessary are stored on your browser as they are as essential for the working of basic functionalities of the website. A more detailed discussion of how recursion works leads to an understanding of how recursion can be replaced with iteration and stacks.
The Case Study develops and implements the Quick-Sort algorithm. Chapter 8 introduces binary search trees as a way to arrange data, giving the flexibility of a linked structure with O log2N insertion and deletion time. In order to build on the previous chapter and exploit the inherent recursive nature of binary trees, the algorithms first are presented recursively.
After all the operations have been implemented recursively, we code the insertion and deletion operations iteratively to show the flexibility of binary search trees. A nonlinked array-based binary tree implementation is described. The Case Study discusses the process of building an index for a manuscript and implements the first phase. Chapter 9 presents a collection of other branching structures: priority queues implemented with both lists and heaps , graphs, and sets.
The graph algorithms make use of stacks, queues, and priority queues, thus both reinforcing earlier material and demonstrating how general these structures are. If the item is not in the list, it is not in the set. Chapter 10 presents a number of sorting and searching algorithms and asks the question: Which are better?
The sorting algorithms that are illustrated, implemented, and compared include straight selection sort, two versions of bubble sort, quick sort, heap sort, and merge sort. The sorting algorithms are compared using Big-O notation. The discussion of algorithm analysis continues in the context of searching. Previously presented searching algorithms are reviewed and new ones are described.
Hashing techniques are discussed in some detail. Finally, radix sort is presented and analyzed. These goals are tested in the exercises at the end of each chapter. Chapter Exercises Most chapters have more than 35 exercises. Approximately one-third of the exercises are answered in the back of the book.
Case Studies There are seven case studies. Each includes a problem description, an analysis of the problem input and required output, and a discussion of the appropriate data types to use. Several of the case studies are completely coded and tested. Others are left at various stages in their development, requiring the student to complete and test the final version.
The source code for the completed case studies and the partial source code for the others is also available. Updated for this edition, the TestBank questions can be edited and supplemented, and answers are provided for all pre-made questions.
Austin State University. Thanks also to all of you who took the time to answer our electronic survey concerning this third edition. Thanks also to the students at Uppsala University in Sweden who used the final draft of the manuscript of the second edition in a course in the fall of Because non-English readers see what is written, not what they expect to see, their comments were invaluable in cleaning up ambiguous wording.
Thanks to my husband Al, our children and grandchildren too numerous to name, and our dogs, Maggie, who keeps my feet warm, and Chrissie, whose role in life is to keep the house in turmoil and mud. A virtual bouquet of roses to the people who have worked on this book: Mike and Sigrid Wile, along with our Jones and Bartlett family. Amy, thank heavens this production schedule was a little more leisurely than the last—but not by much!
Preface 1 Software Engineering Principles 1 1. Contents 6. Now that you are starting your second or third? In this chapter, we review the software design process and the verification of software correctness. In Chapter 2, we review data design and implementation.
As a beginning student of computer science, you wrote programs that solved relatively simple problems. You may have learned a programming methodology that took you from the problem description that your instructor handed out all the way through the delivery of a good software solution. Programmers have created many design techniques, coding standards, and testing methods to help develop high-quality software. But why bother with all that methodology? Why not just sit down at a computer and write programs?
If the degree of our programming sophistication never had to rise above the level of trivial programs like summing a list of prices or averaging grades , we might get away with such a code-first technique or, rather, lack of technique. Some new programmers work this way, hacking away at the code until the program works more or less correctly—usually less. As your programs grow larger and more complex, however, you must pay attention to other software issues in addition to coding.
If you become a software professional, someday you may work as part of a team that develops a system containing tens of thousands, or even millions, of lines of code. Rather, many activities take place concurrently.
We may code one part of the solution while we design another part, or define requirements for a new version of a program while we continue testing the current version.
Often a number of people may work on different parts of the same program simultaneously. Keeping track of all these activities is not an easy task. We use the term software engineering to refer to the discipline concerned with all Software engineering The discipline devoted to the aspects of the development of high quality design, production, and maintenance of computer prosoftware systems. It encompasses all variagrams that are developed on time and within cost estitions of techniques used during the software mates, using tools that help to manage the size and life cycle plus supporting activities such as complexity of the resulting software products documentation and teamwork.
A software Software process A standard, integrated set of software process is a specific set of interrelated softengineering tools and techniques used on a project or by ware engineering techniques, used by a peran organization son or organization to create a system.
What makes our jobs as programmers or software engineers challenging is the tendency of software to grow in size and complexity and to change at every stage of its development.
A good software process uses tools to manage this size and complexity effectively. Usually a programmer takes advantage of several toolboxes, each containing tools that help to build and shape a software product. Hardware One toolbox contains the hardware itself: the computers and their peripheral devices such as monitors, terminals, storage devices, and printers , on which and for which we develop software.
Ideaware A third toolbox is filled with the shared body of knowledge that programmers have collected over time. Recall that an algorithm is a step-by-step description of the solution to a problem. How we choose between two algorithms that carry out the same task often depends on the requirements of a particular application.
Ideaware contains programming methodologies such as top-down and object-oriented design and software concepts, including information hiding, data encapsulation, and abstraction. It also contains some tools for measuring, evaluating, and proving the correctness of our programs.
We devote most this book to exploring the contents of this third toolbox. Artists and composers are creative, yet their innovations are grounded in the basic principles of their crafts. Similarly, the most creative programmers build high-quality software through the disciplined use of basic programming tools. Goals of Quality Software Quality software entails much more than a program that somehow accomplishes the task at hand.
A good program achieves the following goals: 1. It works. It can be modified without excessive time and effort. It is reusable. It is completed on time and within budget. Goal 1: Quality Software Works The program must do the task it was designed to perform, and it must do it correctly and completely. Thus the first step in the development process is to determine exactly what the program is required to do. The specifications tell exactly what the program does, but not how it is done.
Sometimes your instructor will provide detailed specifications; other times you may have to write them yourself, based on the requirements definition, conversations with your instructor, or guesswork.
We discuss this issue in more detail later in this chapter. How do you know when the program is right? In addition, it should be usable. For instance, if the program needs to receive data from a person sitting at a terminal, it must indicate when it expects input.
Indeed, creating a good user interface is an important subject in software engineering today. Finally, Goal 1 means that the program should be as efficient as it needs to be. We would never deliberately write programs that waste time or space in memory, but not all programs demand great efficiency.
When they do, however, we must meet these demands or else the programs will not satisfy the requirements. Closer to home, if a desktop-publishing program cannot update the screen as rapidly as the user can type, the program is not as efficient as it needs to be.
Changes occur in every phase of its existence. Software gets changed in the design phase. When your instructor or employer gives you a programming assignment, you begin to think of how to solve the problem. The next time you meet, however, you may be notified of a small change in the program description. Software gets changed in the coding phase. You make changes in your program as a result of compilation errors. Sometimes you suddenly see a better solution to a part of the problem after the program has been coded, so you make changes.
Software gets changed in the testing phase. If the program crashes or yields wrong results, you must make corrections. In an academic environment, the life of the software typically ends when a corrected program is turned in to be graded. As you see, software changes often and in all phases of its life cycle. Knowing this fact, software engineers try to develop programs that are modified easily. What makes a program easy to modify?
First, it should be readable and understandable to humans. Before it can be changed, it must be understood. A well-designed, clearly written, well-documented program is certainly easier for human readers to understand.
Almost every organization has its own policy for documentation. Reading a well-written program can teach you techniques that help you write good programs. Second, the program should readily be able to withstand small changes. The key idea is to partition your programs into manageable pieces that work together to solve the problem, yet remain relatively independent.
The design methodologies reviewed later in this chapter should help you write programs that meet this goal. Therefore, it is important to realize as much value from the software as possible.
One way to save time and effort when building a software solution is to reuse programs, classes, functions, and other components from previous projects. By using previously designed and tested code, you arrive at your solution sooner and with less effort. Alternatively, when you create software to solve a problem, it is sometimes possible to structure that software so it can help solve future, related problems. By doing so, you gain more value from the software created. Creating reusable software does not happen automatically.
It requires extra effort during the specification and design phases. To be reusable, software must be well documented and easy to read, so that a programmer can quickly determine whether it can be used for a new project. It usually has a simple interface so that it can easily be plugged into another system. It is also modifiable Goal 2 , in case a small change is needed to adapt it to the new system. When creating software to fulfill a narrow, specific function, you can sometimes make the software more generally usable with a minimal amount of extra effort.
In this way, you increase the chances that you can reuse the software later. For example, if you are creating a routine that sorts a list of integers into increasing order, you might generalize the routine so that it can also sort other types of data. Furthermore, you could design the routine to accept the desired sort order, increasing or decreasing, as a parameter.
You probably have grieved over an otherwise perfect program that received only half credit—or no credit at all—because you turned it in one day late. Although the consequences of tardiness may seem arbitrary in the academic world, they are significant in the business world. A patient database system for a new hospital must be installed before the hospital can open.
A company generally budgets a certain amount of time and money for the development of a piece of software. As a programmer, you are paid a salary or an hourly wage. The extra expenditure in salary is not the only cost, however. Other workers may be waiting to integrate your part of the program into the system for testing.
If the program is part of a contract with a customer, monetary penalties may be assessed for missed deadlines. If it is being developed for commercial sales, the company may be beaten to the market by a competitor and eventually forced out of business.
Once you have identified your goals, what can you do to meet them? Where should you start? Software engineers use many tools and techniques. In the next few sections of this chapter, we review some of these techniques to help you understand, design, and code programs. Specification: Understanding the Problem No matter which programming design technique you use, the first steps are always the same.
Imagine the following all-too-familiar situation. On the third day of class, you are given a page description of Programming Assignment 1, which must be running perfectly and turned in by noon, one week from yesterday. You read the assignment and realize that this program is three times larger than any program you have ever written. What is your first step?
The responses listed here are typical of those given by a class of computer science students in such a situation: 1. Students who adopt Response 3 will find their education progressing rather slowly. Response 2 may seem to be a good idea, especially considering the deadline looming ahead. Resist the temptation, though—the first step is to think. Before you can come up with a program solution, you must understand the problem.
Read the assignment, and then read it again. Ask questions of your instructor or manager, or client. Starting early affords you many opportunities to ask questions; starting the night before the program is due leaves you no opportunity at all. The problem with writing first is that it tends to lock you into the first solution you think of, which may not be the best approach.
Chances are that a disk drive, network, or printer will fail that day! Data structures and algorithms textbooks tend to fall into one of two categories: teaching texts or encyclopedias.
Books that attempt to do both usually fail at both. This book is intended as a teaching text. I believe it is more important for a practitioner to understand the principles required to select or design the data structure that will best solve some problem than it is to memorize a lot of textbook implementations. Hence, I have designed this as a teaching text that covers most standard data structures, but not all.
A few data structure that are not widely adopted are included to illustrate important principles. Some relatively new data structures that should become widely used in the future are included.
Within an undergraduate program, this textbook is designed for use in either an advanced lower division sophomore or junior level data structure course, or for a senior level algorithms course.
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