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COURSE
SYLLABUS |
Prerequisites:
COP 3330: Object-Oriented Programming, and MAD 2104: Discrete Mathematics. These pre-requisites will not be waived. Pre or Corequisite: CDA 3100: Computer Organization I.
Class Schedule:
Activity Day Time Location Lecture MWF 12:20 pm - 1:10 pm HWC 3100 Recitation 1 M 10:10 am - 11:00 am LOV 301 Recitation 2 W 10:10 am - 11:00 am HTL 217 Recitation 3 W 11:10 am - 12 noon LOV 301 Recitation 4 W 1:25 pm - 2:15 pm LOV 301 Contact information:
Instructor: Ashok Srinivasan Office hours: M 11 am - 12 noon, R 2 pm - 3 pm. I am also usually available in my office, and you can feel free to meet me except before class. Alternatively, you may schedule an appointment, either by email or by phone. Office: 169, Love Building Phone: 644-0559 Email: asriniva AT cs.fsu.edu
Teaching Assistants:
Shafayat Rahman Soheila Abrishami Office hours: M 11:00 am - 12 noon R 11:30 am - 12:30 am Office: MCH 106 B MCH 106 C Phone: N/A N/A Email: rahman AT cs.fsu.edu abrisham AT cs.fsu.edu Course material:
Required Material:
- Mark Allen Weiss, Data Structures and Algorithm Analysis in C++, third or fourth edition, Addison Wesley 2005, ISBN 0 321-44146-X.
- Online course web pages: www.cs.fsu.edu/~asriniva/courses/DS14 and through Blackboard (http://campus.fsu.edu).
- Code examples: Example code will be made available under the ~cop4530/fall14 directory and subdirectories on the Computer Science file server.
Optional reference material:
- Deitel, H.M. and Deitel, P.J. (1998). C++ How to Program (any edition). New Jersey: Prentice Hall. ISBN 0-13-528910-6 or any similar C++ book
Online resources:
- C++ documentation: www.cplusplus.com.
- Single Unix Specification: http://www.unix.org/single_unix_specification.
- Emacs tutorial: www.math.utah.edu/computing/unix/emacs.html
- FSU User Services Site Licenses: http://its.fsu.edu/Software/SoftwareLicensing.html
Computer accounts:
- You will need a computer account in the Computer Science department. Please follow the procedure outlined in http://www.cs.fsu.edu/sysinfo/newstudent.html to obtain an account, if you do not have one already.
- Class email will be sent to your FSU account (@fsu.edu). So please obtain an FSU account, if you do not have one already. If you use another email account (such as yahoo), then you must forward your FSU email to that account. Instructions on obtaining an account and forwarding email are available through the FSU helpdesk.
- The subject line in any email you send me should start with
COP 4530
.- You will need to use Blackboard (http://campus.fsu.edu).
Course rationale:
So far, you have acquired proficiency in programming. This course will start the process of your transformation from a programmer to a computer scientist. One of the important tasks of a computer scientist is to make efficient use of computational resources. This course will teach you about different ways of organizing the data to facilitate such efficient use, and will also discuss efficient techniques to perform some fundamental operations in computer science. A subsequent course on Algorithms, COP 4531, will teach you to use the techniques discussed in this course to solve commonly encountered computer science problems efficiently. Both these courses will also teach you to analyze the efficiency, and prove the correctness, of your program in a mathematically rigorous manner. Material you learn in these two courses is critical to your becoming a good software developer later.Course description:
This IS NOT a course on object-oriented programming!
This is a course about efficiency of programs and programming. In this course, we will pursue various meanings of "efficient". It is efficient to:
Furthermore, in many applications, correctness is the ultimate form of efficiency, while in others efficiency means getting the best result possible in the limited time (or space) available.
- minimize the run time of code, especially code that is destined for re-use.
- minimize the memory and storage needs of code, recognizing that there may be a trade-off between speed and memory requirements.
- spend less time writing a program of equal quality. In fact, it is even more efficient to spend the same time writing a program of higher quality.
- re-use code, instead of re-writing code.
- select only the linguistic features you need without having to use costly extra features you do not need.
Efficiency can happen at different levels. Take code:
- Source code can be small in size, easy to read, and easy to understand.
- Executable code can be fast or compact (or both).
- The code production process can be efficient by applying good software engineering methodology; savings in human effort too represent efficiency. Effort can be saved by good design, by careful (error-free) programming, and by re-using both code itself and patterns of problem solving that are known to be successful.
- Code can run efficiently, in either a temporal or spatial sense.
All these ideas of efficiency are central to this course. It is also true that all of these ideas of efficiency are fundamental to the design and specification of the C++ language, which is one of many reasons C++ is a good choice for the core language in our curriculum and for this course.
The three topics mentioned in the title of the course are:
- Data structures
- We will discuss data structures in abstract terms, as abstract data types (ADTs), but we will also implement them concretely, using C++.
- Algorithms
- Algorithms are formalizations of processes that result in predictable and desirable outcomes. They are used in a variety of contexts. Particularly, data structures are made usable by implementing algorithms for searching, sorting, and indexing the structures.
- Generic programming
- Generic programming is the science of component re-use. We will explore coding for re-use of both data structures and algorithms in C++. Coding for re-use and re-use of code are important aspects of software engineering.
We will also have several substantial programming projects that involve the implementation and use of data structures, algorithms, and generic programming.
Learning objectives:
At the end of this course, you should be able to accomplish the objectives given below. Furthermore, since the tasks mentioned below are those that every computer scientist is expected to be familiar with, it will help you if you learn it well enough that you have a permanent working knowledge of the material discussed.
Data StructuresAlgorithms
- Define and use the following abstract data types (ADTs) as generic containers:
Positional ADTs: vector, list, deque, stack, queue, graph, digraph
Associative ADTs: table, map (associative array), priority queue, set- Implement these ADTs, including performance constraints (in terms of runtime complexity) on the operations.
Note that this implies the detailed study of trees of several types as implementation structures and the use of template classes as well as the elementary study of algorithms and their complexity.You should be able to accomplish the following:
Generic Programming
- Show the steps performed by algorithms that use the data structures given above, and of their simple variants.
- Prove the correctness of algorithms that use the data structures given above, and of their simple variants.
- Perform time and space complexity analysis of algorithms that use the data structures given above, and of their simple variants.
You should be able to accomplish the following:
Attaining these objectives will enable you to:
- Implement a given data structure as a generic container, using class templates with typename template parameters.
- Implement a given algorithm generically, using function templates with iterator template parameters.
- Write code that performs many of the fundamental operations of Computer Science efficiently.
- Modify the techniques we discuss, when an application on which you are working is unable to use the techniques directly.
- Write code that is re-usable.
Your responsibilities:
- Deadlines and instructions
- Following the same professional guidelines that you will encounter in business, there are strict deadlines, and instructions that must be followed. Please read instructions carefully, and schedule your activities so that you submit assignments well in time. You should check your FSU email account and the class web page regularly, and note other announcements, on-line and in class.
- Class participation and quizzes
- I will ask you questions in class and through online quizzes: (i) review questions on the previous lecture, and (ii) questions on the material currently being discussed, in order for me to obtain feedback on how well you understand the material. You should be prepared to answer these questions, and should also participate by asking questions, suggesting ideas, and performing in-class assignments that I give. This will count toward your class participation grade. Of course, you cannot participate in class unless you attend it! The recitations too form an important component of the course. You will be given quizzes during most recitations, on material covered since the previous quiz, and you will also be asked to write small programs and perform other tasks.
- Reading assignments
- After each lecture, you will be given a reading assignment pertaining to that lecture. You should read these, and also practice with example codes that we supply. New material builds on the old ones. So, if you have trouble with some material, please get help through the discussion board on Blackboard, or from a teaching assistant or me, before the next class. You should also peruse the material for the next lecture, and be prepared to answer questions on it, which I will provide in advance. I expect that you will need to spend between one and two hours studying, for each lecture. The programming assignments and exams will consume additional time. The following learning components are important, and you may want to verify if you do satisfactorily on these, after studying the material.
- Knowledge: Do you understand the terminology used? Given a data-structure and some data or operations, can you tell how the data is represented? Given an algorithm and its input, can you describe the steps carried out by the algorithm and the output? Given a data structure or algorithm, can you write C++ code for it? Given a data-structure and some operations on it, or an algorithm, can you give the time and space complexity?
- Understanding: If some aspect of a data-structure, an operation on it, or an algorithm, were modified, can you analyze the time complexity? If some aspect of an operation on a data-structure, or an algorithm, were modified, can you prove or disprove its correctness? In order to answer these questions, you need to understand how each component of an algorithm affects the time complexity, and why each component of an algorithm is important for its correctness. After you learn about what an algorithm does (and have, thus, acquired "knowledge"), it will be useful for you to think of different things that can be changed, and see how that will affect the time complexity or correctness.
- Application: Given a real life, or artificial, problem, can you decide on suitable data structures and algorithms from those we have studied, to solve that problem?
- Creativity: Can you modify algorithms that we have studied, to make them more efficient for special situations? Given a problem for which our algorithm is not valid as designed, can you modify the algorithm to solve the problem, and then prove the correctness of your solution, and analyze its time complexity? Can you use multiple data structure and algorithms from those that we have studied, to solve a new problem?
- Homework assignments
- You will have five programming assignments with around two weeks to work on each one. They will be announced on Blackboard. We will also discuss them during the recitations. Assignment submission instructions are available at www.cs.fsu.edu/~asriniva/courses/DS14/HWinstructions.html. The programming assignments will be substantially more difficult than those in previous programming courses, and require substantially more time and effort. Please start working on the assignments as soon as they are announced, if you wish to complete them!
Course calendar:
Notes: 1. The recitation material presented Monday will be repeated in the recitations Wednesday. 2. If a recitation falls on a holiday, then you can work on the exercises that will be available through the course calendar. 3. There will be quizzes during most recitations, which will be on material covered since the previous quiz. These quizzes will not be announced in advance. 4. See the document on Class Participation for guidance on class participation grades.
Week Lecture Chapter Assignments 1 Recitation Discuss assignment 1, compilation, and makefiles. Assignment 1 announced 28 Aug 25 Aug 1. Introduction, math review, sections 1.1 - 1.2 27 Aug 2. Recursion, section 1.3 29 Aug 3. C++ review, section 1.4-1.5.
Quiz on C++ and Unix: see Initial quiz to help prepare for it.2 Recitation Discuss assignment 1. None 1 Sep No class -- labor day. 3 Sep 4. C++ templates, sections 1.6-1.7 5 Sep 5. Algorithm analysis, chapter 2 3 Recitation Using a debugger, discuss assignment 2 Assignment 1 due 11 Sep 8 Sep 6. Algorithm analysis, chapter 2 10 Sep 7. Vectors, sections 3.1-3.4; Lists, sections 3.2, 3.3, 3.5 12 Sep 8. Stacks and Queues, sections 3.6-3.7 4 Recitation Time complexity analysis
Assignment 2 announced 16 Sep15 Sep 9. Self-organizing lists, class notes 17 Sep 10. STL, class notes 19 Sep 11. Iterators, class notes 5 Recitation Discuss assignment 2 - Analysis of recursion None 22 Sep 12. Trees and tree traversals, section 4.1 24 Sep 13. Binary trees, section 4.2 26 Sep 14. Binary search trees, section 4.3, 4.6 6 Recitation Midterm review Assignment 2 due 30 Sep
Assignment 3 announced 30 Sep29 Sep 15. Binary search trees, section 4.3 1 Oct 16. Binary search trees, section 4.3 3 Oct Midterm review 7 Recitation Discuss midterm solutions None 6 Oct Midterm 8 Oct 17. AVL trees, section 4.4 10 Oct 18. AVL trees, section 4.4 8 Recitation Discuss assignment 4 Assignment 3 due 16 Oct
Assignment 4 announced 16 Oct13 Oct 19. AVL trees, section 4.4 15 Oct 20. Self-adjusting trees, class notes 17 Oct 21. B-trees, section 4.7 9 Recitation Profiling code None 20 Oct 22. Proofs of tree properties 22 Oct 23. Sets and maps, section 4.8 24 Oct 24. Hash table introduction, sections 5.1, 5.2, 5.6 10 Recitation Selecting a data structure for a problem None 27 Oct 25. Hash tables with chaining, section 5.3 29 Oct 26. Hash tables without linked lists, section 5.4 31 Oct 27. Rehashing, section 5.5 11 Recitation OpenMP Assignment 4 due 6 Nov
Assignment 5 announced 6 Nov3 Nov 28. Priority queues, chapter 6 5 Nov 29. Priority queues, chaper 6 7 Nov 30. Priority queues, chapter 6 12 Recitation Discuss assignment 5 None 10 Nov 31. Review time complexity (continued) 12 Nov Review time complexity (completed) 14 Nov 32. Sorting, chapter 7 13 Recitation Final exam review None 17 Nov 33. Sorting, chapter 7 19 Nov 34. Sorting, chapter 7 21 Nov 35. Sorting, chapter 7 14 Recitation No recitation Assignment 5 due 25 Nov 24 Nov 36. Graph algorithms, chapter 9 26 Nov No class -- Thanksgiving. 28 Nov No class -- Thanksgiving. 15 Recitation Final exam review None 1 Dec 37. Graph algorithms, chapter 9 3 Dec 38. Graph algorithms, chapter 9 5 Dec Final exam review 16 12 Dec Friday 7:30 am - 9:30 am, final exam Grading criteria:
The overall grade for COP 4530 is an average of two equally weighted parts: (i) tests, and (ii) assignments. Tests consist of a midterm, a final exam, several quizzes, and class participation. Assignments consist of five programming assignments, with some theoretical and experimental components to some of them.
There are 1000 total points that may be earned in the course, distributed as shown in Table 1. You must earn at least 350 test points and 350 assignment points in order to get a course grade of C- or better. You must also obtain a grade of C- or better on certain components of assignment 2, as explained below, in order to obtain a course grade of C- or higher. Once meeting these two constraints, the final grade is determined using Table 2.
Certain components of assignment 2 in this course have been designated by the Department of Computer Science for assessment of the following expected outcomes for its degree programs, as required by our accreditation agencies, the university, and the State of Florida: (i) Recursive Algorithm Use and (ii) Data Structure Knowledge. Departmental policy does not permit a final grade of "C-" or better to be assigned unless the student has at earned a grade of "C-" or better on each of these components, regardless of performance on other work in the course.
Table 1: Course Points Item Points/Item Item Total Total \ tr>Quizzes 50 Class Participation 50 Midterm 150 150 Final Exam (comprehensive) 250 250 500 Assignments (see note 2) 100 500 500
Table 2: Letter Grades Points Grade 920 - 1000 A 900 - 919 A- 880 - 899 B+ 820 - 879 B 800 - 819 B- 780 - 799 C+ 720 - 779 C 700 - 719 C- 680 - 699 D+ 620 - 679 D 600 - 619 D- 0 - 599 F NOTES: (1) You must earn at least 350 points in each of the components: (i) tests and (ii) Assignments, to be awarded a course grade of C- or better. For example, if you obtain 500 points on the assignments, but only 300 in the rest, then you will not get a B-. Instead, you will get a D+, since that is the highest grade for which you will be eligible without obtaining 350 points in each of the two components, assignments and tests. (2) You must obtain a C- or higher in each of specific components of assignment 2 in order to obtain a course grade of C- of higher. (3) CGS 5425 students will not have quizzes. They will, instead, have double the weight for class participation.
Programming assignment Assessment
Programming assignments will be assessed using Table 3 as a rough guide.
Table 3: Programming assignment assessment criteria Criterion Percentage Points Range Project compiles and executes simple sample inputs correctly 0 ... 20 Baseline test passed 0 ... 20 Advanced test passed 0 ... 20 Project meets requirements 0 ... 20 Good design and readability 0 ... 10 Project log and project submitted as specified 0 ... 10 The first three criteria will be assessed objectively through automated testing. A member of the instructional staff will then assess for the latter three criteria. Please note carefully the following important items:
- You must understand your project work. If you are asked to explain your work, and you are unable to do so, you may be assigned a grade of zero.
- The above grading guidelines are for projects that are reasonably correct. For example, if your code is very readable but does not have anything to do with the problem you were asked to solve, then you will not get any point!
Course policies:
Attendance Policy:
The university requires attendance in all classes, and it is also important to your learning. The attendance record may be provided to deans who request it. If your grade is just a little below the cutoff for a higher grade, then your attendance will be one of the factors that we consider in deciding whether to "bump" you up to the higher grade. Three or fewer unexcused absences in lectures and recitations will be considered good attendance.Excused absences include documented illness, deaths in the immediate family and other documented crises, call to active military duty or jury duty, religious holy days, and official university activities. Accommodations for these excused absences will be made and will do so in a way that does not penalize students who have a valid excuse. Consideration will also be given to students whose dependent children experience serious illness.
You should let me know in advance, when possible, and submit your documentation. You should make up for any materials missed due to absences.
Missed exam Policy:
A missed exam will be recorded as a grade of zero. We will follow the university rules regarding missed final exams (see http://registrar.fsu.edu/dir_class/fall/exam_schedule.htm), for all the exams, including the final exam.Late Assignment Policy:
In order to enable us to provide timely solutions to assignments, we have the following policy regarding submission of late assignments.
- An assignment that is turned in no more than 48 hours late will be scored with a 20% penalty.
- An assignment that is turned in more than 48 hours late will receive the score of zero, though we will review it and comment on it.
Grade of 'I' Policy:
The grade of 'I' will be assigned only under the following exceptional circumstances:
- The final exam is missed with an accepted excuse for the absence. In this case, the final exam must be made up during the first two weeks of the following semester.
- Due to an extended illness or other extraordinary circumstance, with appropriate documentation, the student is unable to participate in class for an extended period. In this case, arrangements must be made to make up the missed portion of the course prior to the end of the next semester.
Professional ethics:
You will gain confidence in your ability to design and implement algorithms only when you write the code yourself. On the other hand, one does learn a lot through discussions with ones peers. In order to balance these two goals, I give below a list of things that you may, and may not, do.Things you may not do: You should not copy code from others. This includes directly copying the files, replacing variable names in their code with different names, altering indentation, or making other modifications to others' code, and submitting it as your own. (You may also wish to note that many of the modifications that make codes look very different in a higher level language, yield lower level representations that are very close, and are hence easy to detect.) Furthermore, you should take steps to ensure that others cannot copy code from you -- in particular, you should have all permissions on assignment files and directories set off for others.
Things you may do: You may discuss specific problems related to use of the computer, useful utilities, and some good programming practices, with others. For example, you may ask others about how to submit your homework, or how to use the debugger or text editor.
Honor Code: The Florida State University Academic Honor Policy outlines the University's expectations for the integrity of students' academic work, the procedures for resolving alleged violations of those expectations, and the rights and responsibilities of students and faculty members throughout the process. Students are responsible for reading the Academic Honor Policy and for living up to their pledge to be honest and truthful and [to] strive for personal and institutional integrity at Florida State University. (Florida State University Academic Honor Policy can be found at http://fda.fsu.edu/content/download/21140/136629/AHPFinal2014.pdf .)
Plagiarism:
- Plagiarism is "representing another's work or any part thereof, be it published or unpublished, as ones own. For example, plagiarism includes failure to use quotation marks or other conventional markings around material quoted from any source" (Florida State University General Bulletin 1998-1999, p. 69). Failure to document material properly, that is, to indicate that the material came from another source, is also considered a form of plagiarism. Copying someone else's program, and turning it in as if it were your own work, is also considered plagiarism.
ADA: Students with disabilities needing academic accommodation should: (1) register with and provide documentation to the Student Disability Center, and (2) bring a letter to the instructor indicating the need for accommodation and what type. This should be done during the first week of class. This syllabus and other class materials are available in alternative format upon request. For more information about services available to FSU students with disabilities, contact:
Student Disability Resource Center
874 Traditions Way
108 Student Services Building
Florida State University
Tallahassee, FL 32306-4167
(850) 644-9566 (voice)
(850) 644-8504 (TDD)
sdrc@admin.fsu.edu
http://www.disabilitycenter.fsu.eduSYLLABUS CHANGE POLICY:
Except for changes that substantially affect implementation of the evaluation (grading) statement, this syllabus is a guide for the course and is subject to change with advance notice.
Last modified: 31 Aug 2014