AS

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)