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CS6515 Exam 1 – 100% Solved Questions | Dynamic Programming, Divide & Conquer, FFT, Roots of Unity | 2025/2026

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This document contains fully solved questions and answers for Exam 1 of CS6515 - Graduate Algorithms, tailored for the 2025/2026 academic year. It focuses on key algorithmic strategies such as Dynamic Programming (DP) and Divide & Conquer (DC), as well as advanced mathematical tools like Fast Fourier Transform (FFT) and roots of unity. Through detailed recurrence relations, pseudocode, runtime analysis, and step-by-step explanations, students are guided through complex problems commonly featured in graduate-level algorithm exams. Topics include: Solving DP problems using subproblem classification and recurrence relationships Master Theorem and solving recurrence relations FFT and inverse FFT algorithms, matrix construction, and polynomial multiplication Imaginary numbers, polar and Cartesian coordinate transformations, and Euler’s formula Classic problems: Knapsack (with and without repetition), Longest Increasing Subsequence (LIS), Longest Common Subsequence (LCS), Edit Distance, Matrix Multiplication Algorithm runtimes and complexity analysis of sorting and searching strategies (MergeSort, QuickSort, Binary Search) This study guide is best suited for: Graduate computer science students Learners preparing for Georgia Tech’s CS6515: Introduction to Graduate Algorithms Individuals preparing for algorithm-heavy coding interviews or competitive programming contests Students in U.S. universities enrolled in advanced algorithm or theoretical CS courses The Q&A format makes this document ideal for quick reference and targeted revision, ensuring deep understanding of both conceptual theory and practical application. Keywords: CS6515, algorithms exam, dynamic programming, divide and conquer, FFT, roots of unity, recurrence relations, master theorem, Euler’s formula, pseudocode, knapsack problem, edit distance, LCS, LIS, polynomial multiplication, merge sort, quick sort, Georgia Tech, algorithm runtimes, matrix multiplication, O(n log n), O(n²)

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CS6515 - Algorithms- Exam 1 2025/2026
Exam Questions and Answers | A+
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Steps to solve a Dynamic Programming Problem - 🧠 ANSWER ✔✔1.

Define the Input and Output.




2. Define entries in table, i.e. T(i) or T(i, j) is...




3. Define a Recurrence relationship - Based on a subproblem to the main

problem. (hint: use a prefix of the original input 1 < i < n).




4. Define the Pseudocode.

,5. Define the Runtime of the algorithm. Use Time Function notation here =>

T(n) = T(n/2) + 1...


DP: Types of Subproblems (4) - 🧠 ANSWER ✔✔Input = x1, x2, ..., xn


1) Subproblem = x1, x2, ..., xi ; O(n)

2) Subproblem = xi, xi+1, ..., xj ; O(n^2)




Input = x1, x2, ..., xn; y1, y2, ..., ym

1) Subproblem = x1, x2, ..., xi; y1, y2, ..., yj ; O(mn)




Input = Rooted Binary Tree

1) Subproblem = Smaller rooted binary tree inside the Input.


DC: Geometric Series - 🧠 ANSWER ✔✔Given r = common ratio and a =

first term in series

=> a + ar + ar^2 + ar^3 + ... + ar^(n-1)




=> a * [(1 - r^n) / (1-r)]

, DC: Arithmetic Series - 🧠 ANSWER ✔✔Given d = common difference and a

= first term in series => a + (a + d) + (a + 2d) + ... + (a + (n-1)d




Sum = n/2 * [2*a + (n-1)d]


DC: Solving Recurrences - Master Theorem - 🧠 ANSWER ✔✔If T(n) =

aT([n/b]) + O(n^d) for constants a>0, b>1, d>=0:




T(n) = {

O(n^d) if d > logb(a)

O((n^d)logn) if d = logb(a)

O(n^(logb(a))) if d < logb(a)

}


Nth roots of Unity - 🧠 ANSWER ✔✔(1, 2*PI*j/n) for j = 0, 1, ..., n-1


*Around the Unit Circle!


Steps to solve for FFT - 🧠 ANSWER ✔✔1) Write out Matrix Coefficient

Form based on n (size of input) Mn(w) = [ 1 1 ... 1



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