- Syllabus
- Course work section of the instructor's page for students, esp. regarding the following: announcements, attendance, holidays, in-class/take-home exercises, make-up policy, and academic integrity.
- On-line course handbook (this page)

There are two non-CS courses that have significant overlap with CMSC210. One is MAT200 (Discrete Math) and the other is PHL120 (Logic). If you have taken MAT200, you will see substantial overlap with CMSC210. If you have taken PHL120, you will feel the logic part of CMSC210 redundant. These students must consult the instructor before or early in the semester so that they can focus on the topics/approaches that are not covered in these courses. Special arrangements can be (and should be) made.

Just for your information, here is a list of discrete math (and related) textbooks that have been/could be used for this course:

*Mathematical Methods in Linguistics*by Barbara H. Partee, Alice G. Ter Meulen, and Robert Wall. Kluwer. 1990. [used in Sections 3 & 4, Fall 2002]*Discrete Mathematical Structures, 4th ed*. byBernard Kolman, Robert C. Busby, and Sharon Ross . Prentice Hall. 1999. [used in Sections 2 & 5, Fall 2002]*Introduction to Abstract Mathematics, 2nd ed*. by John F. Lucas. Ardsley House. 1990. [text for MAT200; similar coverage]*Discrete Mathematics, 5th ed*. by Richard Johnsonbaugh. Prentice Hall. 2001. [used in the past; older edition available in the TCNJ library]*Discrete Mathematics and its Applications, 5th ed*. by Kenneth H. Rosen. McGraw-Hill. 2003. [broad coverage (except for general ideas about algebra)]*Discrete Mathematical Structures for Computer Science*by Ronald E. Prather. Houghton Mifflin. 1976. [more materials on algebra, less on logic; available in the TCNJ library]*Discrete Structures of Computer Science*by Leon S. Levy. John Wiley & Sons. 1980. [good motivational examples; also as*Fundamental Concepts of Computer Science*, 1988; available in the TCNJ library]*Discrete Mathematics in Computer Science*by Donald F. Stanat and David F. McAllister. Prentice Hall. 1977. [coverage close to this course; available in the TCNJ library]

*Representation and Invariance of Scientific Structure*by Patrick Suppes. CSLI. 2002. [contains a lot of ideas discussed in this course*in detail*; probably readable and useful after this course (at least some part of it)]*Specification of Abstract Data Types*by Jacques Loeckx, Hans-Dieter Ehrich, and Markus Wolf. John Wiley & Sons. 1996. [emphasizes the connection between logic and algebraic structures]*Formal Specification: Techniques and Applications*by Nimal Nissanke. Springer-Verlag. 1999. [many examples]*Elementary Mathematical Modelling: A Dynamic Approach*by James Sandefur. Brooks/Cole. 2003. [contains many examples of modeling dynamic phenemena]*A Mathematical Introduction to Logic, 2nd ed*. by Herbert B. Enderton. Academic Press. 2000. [classic]*Mathematical Logic*by Stephen Cole Kleene. John Wiley & Sons. 1967. [some discussion on logic-structure connection; available in the library]

*What is Mathematical Logic?*by J. N. Crossley, et al. Dover. 1990. (originally from Oxford Univ. Press in 1972). [short; good to grasp the big picture (but not an introduction)]*Mathematical Logic*by Stephen Kleene. John Wiley & Sons. 1967. [available in the library; ]

*An Introduction to Formal Languages and Automata, 3rd ed*. by Peter Linz. 2001. Jones & Bartlett. [good explanation]

*Handbook of Logic and Proof Techniques for Computer Science*by Steven G. Krantz. Birkhäuser. 2002. [useful as a reference]-
*An Introduction to Information Theory*by Fazlollah M. Reza. Dover. 1994. (originally from McGraw-Hill in 1961). [helpful explanation of the background of information/entropy]

Hypothetical case | Take-home exercises (35%) | Comprehensive exercises (60%) | Project (5%) | Total | Expected grade |

1 | 100% (of 35%) | 90% | 100% | 94% | A |

2 | 90% | 80% | 80% | 84% | B |

3 | 80% | 70% | 60% | 73% | C |

4 | 70% | 60% | 40% | 63% | D |

In order to perform well in this course, you will need to complete nearly all take-home exercises as this component will help you to master the material in a timely manner.

- Introduce real-world problem that can be represented by using discrete math.
- Identify the discrete math concepts needed for the problem.
- Introduce and explain the discrete math concepts.
- Discuss how to apply the concepts to similar problems.
- Summarize the main points.
- Do in-class exercise at any point to appreciate introductory problems, understand the material, and/or review the topics.
- Introduce take-home exercises.

In general, by the evening before each lecture, I will post a preliminary version of lecture notes. Although students are not required to use this information, it might be helpful to bring a printout so that you can take note on it. After each lecture, exercises will be posted as well as a revised version of lecture notes, if necessary.

Students are encouraged to do exercises in groups. However, it would be best if you work on your own and have some answer before discussion.

If necessary, you might also consider Tutoring Center in Forcina Hall Room 145. Their web site is here.

In this class, please bring extra sheets of paper for in-class exercises.

One point raised in the education research literature is that weak students tend to overestimate their achievements and strong students tend to underestimate theirs. It is important that all the students understand their levels as accurately as possible so that they all achieve the course performance goals, through improvements following accurate evaluations. For this reason, I will need to be straightforward about my review of your self-evaluation. Since there are three midterm evaluation workshops, you should be able to compare the evaluations by yourself and me and to reflect it in later self-evaluations.