Lecture 00 - Intro (1)

Lecture 01: Introduction

• Instructor: Yu Yang

• Course: CSE 140 - Foundations of Discrete Structures and Algorithms (Section 010)

• Contact: yuyang@lehigh.edu

General Information

• Class Schedule:

  • Time: 1:35 PM – 2:50 PM, Monday/Wednesday

  • Location: Neville 003

• Office Hours:

  • Instructor: Wednesday/Thursday, 11 AM – 12 PM

  • TA/Graders: To Be Decided (TBD)

Course Material

• Main materials available on CourseSite

• Use Piazza for Q&A (technical questions)

  • Sign up at: https://piazza.com/lehigh/spring2025/cse140

• GradeScope for homework grading

Required Texts

1. Primary Textbook:

   • Title: CSE140: Foundations of Discrete Structures and Algorithms (online)

   • Publisher: zyBooks

   • Access code: LEHIGHCSE140Spring2025 (subscription fee: $64)

2. Supplemental Text:

   • Title: Discrete Mathematics and its Applications, 8th Ed.

   • Author: Kenneth H. Rosen

   • ISBN: 978-1259676512 (ISBN-10: 125967651X)

Grading Breakdown

• Total Course Grades: 100%

  • Participation (Attendance, zyBooks): 10%

  • Homework: 30%

  • Midterm Exams: 30%

  • Final Exam: 30%

• Drop Policy:

  • Drop 3 unexcused attendance records

  • Lowest zyBook activity and homework will be dropped

• Grade Thresholds:

  • 90% guarantees A-, 80% B-, 70% C-, 60% D-

Policies

• No makeup exams or extensions for homework without a valid excuse

• All assignments must be completed individually

• Important to understand the distinction between discussion and writing up assignments

• Adherence to the honor code is required

Importance of CSE 140

• Necessary for degree progression

• Prepares students for CSE 340 Algorithms

• Relevant for industry, academia, and advanced study in areas such as:

  • AI, machine learning, advanced algorithms

  • Understanding of systems related to Internet operations

Course Topics Overview

• Topics covered:

  • Propositional and predicate logic

  • Logical inference

  • Sets, functions, relations

  • Recursion and structural induction

  • Graphs and trees

  • Proof techniques (direct, contrapositive, induction, etc.)

  • Loop invariants

  • Counting, permutations, combinations

  • Pigeonhole principle

Course Objectives

1. Basic Representations in Algorithms:

   • Propositional and predicate logic

   • Sets, functions, relations, matrices, graphs, trees

2. Proving Algorithm Correctness:

   • Logical inference, direct proof, contradiction, induction, and loop invariants

3. Algorithm Analysis:

   • Counting techniques, pigeonhole principle, permutations, complexity analysis

Tentative Course Schedule

• Week 1 (Jan 20): Overview, Propositional Logic

• Week 2: Continued Propositional Logic

• Week 3: Logical Inference

• Week 4: Sets and Functions

• Week 5: Functions (continued)

• Week 6: Exam 1, Review/Catch up

• Week 9: Induction (continued)

• Weeks 10 to 14: Various topics including Boolean Algebra and Graphs

• Week 15: Final revisions and topics on Trees

Next Lecture

• Topic: Propositional Logic

• Feedback form available: https://forms.gle/1a68g47Ah5Xjnb8x8 (livestreamed until semester ends)