FSU Seal

    COURSE SYLLABUS

    COP 4530 / CGS 5425
    Data Structures, Algorithms, and Generic Programming

    Fall 2013

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 11:15 am - 12:05 pm LOV 301
Recitation 2 W 3:35 pm - 4:25 pm LOV 301
Recitation 3 F 11:15 am - 12:05 pm LOV 301

Contact information:

Instructor: Ashok Srinivasan
Office hours: M 3:30 pm - 4:30 pm, W 1:15 pm - 2:15 pm. I am also usually available in my office, and you can feel free to meet me in the afternoons. 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:

 John Nguyen Rajat Raychaudhuri
Office hours: TR 12:30 pm - 1:30 pm MF 2 pm - 3 pm
Office: MCH 114 LOV 267
Phone: TBA TBA
Email: jnguyen AT cs.fsu.edu raychaud AT cs.fsu.edu

Course material:

Required Material:
Optional reference material:
Online resources:
Computer accounts:

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.

Efficiency can happen at different levels. Take code:

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 Structures Algorithms

You should be able to accomplish the following:

Generic Programming

You should be able to accomplish the following:

Attaining these objectives will enable you to:

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: (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/DS13/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 and Friday. 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
26 Aug 1. Introduction, math review, sections 1.1 - 1.2
28 Aug 2. Recursion, section 1.3
30 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
2 Sep No class -- labor day.
4 Sep 4. C++ templates, sections 1.6-1.7
6 Sep 5. Algorithm analysis, chapter 2
3 Recitation Using a debugger, discuss assignment 2 Assignment 1 due 11 Sep
9 Sep 6. Algorithm analysis, chapter 2
11 Sep 7. Vectors, sections 3.1-3.4; Lists, sections 3.2, 3.3, 3.5
13 Sep 8. Stacks and Queues, sections 3.6-3.7
4 Recitation Time complexity analysis
Assignment 2 announced 16 Sep
16 Sep 9. Self-organizing lists, class notes
18 Sep 10. STL, class notes
20 Sep 11. Iterators, class notes
5 Recitation Discuss assignment 3 None
23 Sep 12. Trees and tree traversals, section 4.1
25 Sep 13. Binary trees, section 4.2
27 Sep 14. Binary search trees, section 4.3, 4.6
6 Recitation Midterm review Assignment 2 due 30 Sep
Assignment 3 announced 30 Sep
30 Sep 15. Binary search trees, section 4.3
2 Oct 16. Binary search trees, section 4.3
4 Oct Midterm review
7 Recitation Discuss midterm solutions None
7 Oct Midterm
9 Oct 17. AVL trees, section 4.4
11 Oct 18. AVL trees, section 4.4
8 Recitation Discuss assignment 4 Assignment 3 due 16 Oct
Assignment 4 announced 16 Oct
14 Oct 19. AVL trees, section 4.4
16 Oct 20. Self-adjusting trees, class notes
18 Oct 21. B-trees, section 4.7
9 Recitation Profiling code None
21 Oct 22. Proofs of tree properties
23 Oct 23. Sets and maps, section 4.8
25 Oct 24. Hash table introduction, sections 5.1, 5.2, 5.6
10 Recitation Selecting a data structure for a problem None
28 Oct 25. Hash tables with chaining, section 5.3
30 Oct 26. Hash tables without linked lists, section 5.4
1 Nov 27. Rehashing, section 5.5
11 Recitation OpenMP Assignment 4 due 6 Nov
Assignment 5 announced 6 Nov
4 Nov 28. Priority queues, chapter 6
6 Nov 29. Priority queues, chaper 6
8 Nov 30. Priority queues, chapter 6
12 Recitation Discuss assignment 5 None
11 Nov No class -- Veteran's day
13 Nov 31. Review time complexity
15 Nov 32. Sorting, chapter 7
13 Recitation Final exam review None
18 Nov 33. Sorting, chapter 7
20 Nov 34. Sorting, chapter 7
22 Nov 35. Sorting, chapter 7
14 Recitation No recitation Assignment 5 due 26 Nov
25 Nov 36. Graph algorithms, chapter 9
27 Nov No class -- Thanksgiving.
29 Nov No class -- Thanksgiving.
15 Recitation Final exam review None
2 Dec 37. Graph algorithms, chapter 9
4 Dec 38. Graph algorithms, chapter 9
6 Dec Final exam review
16 10 Dec Tuesday 10 am - 12 noon, 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
    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.

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:

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.

Grade of 'I' Policy:

The grade of 'I' will be assigned only under the following exceptional circumstances:

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://academichonor.fsu.edu/policy/policy.html.)

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.

SYLLABUS 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: 18 Nov 2013