CSCI 340: Computational Models
Spring 2020

Meeting times

Section 1:

  • Tuesday 1:10-3:00PM Roddy Hall Rm 256

  • Thursday 1:10-3:00PM Roddy Hall Rm 256 or Mac Lab (Caputo 131)

Section 2:

  • Tuesday 3:10-5:00PM Roddy Hall Rm 256

  • Thursday 3:10-5:00PM Roddy Hall Rm 256 or Mac Lab (Caputo 131)

Description

This course covers important results in the theory of computer science that provide insight into both the capabilities and limitations of computing machines. Emphasis is placed on the relevance of theoretical results to practical problems such as compiler construction and language processing. Topics include automata, Turing Machines, formal grammars, formal languages, non-computability, and computational complexity. The course includes a laboratory component.

Prerequisite: CSCI 140 and CSCI 162

Textbooks

Introduction to Computer Theory. Daniel I. A. Cohen. Publisher: John Wiley & Sons, Inc. ISBN: 0-471-13772-3

Grading

Exam 1: 20% Exam 2: 20% Exam 3 (given during final exam period): 20% Homework, Quizzes and Labs: 35% Participation and attendance: 5% *Lab absences can result in overall grade deductions (see attendance policy below) Grading will be on a 100 point scale, with 93%=A, 90%= A-, 87%=B+, 83%= B, etc. You must complete all exams, labs, and assignments in order to pass the course.

**Participation and attendance: Of the 5%, 3% will be based on lecture attendance (lab attendance is separate, see attendance policy on syllabus) and 2% on participation.

Earning the attendance credit: 0 or 1 unexcused absences: full 3% 2 unexcused absences: 2% 3 unexcused absences: 1% >3 unexcused absences: 0% ** The attendance requirement will be frozen after spring break (no further absences will be counted and participation will be recorded as your participation before spring break). However, if you wish to improve your participation grade, attend and participate in the live Zoom class sessions at 3:10pm on T-Th. Lack of attendance there will not hurt you, but attendance and participation will boost your grade.

Additional Information
Syllabus
Assignments
Resources

2018 — Stephanie Schwartz — Millersville University