The Complete DAA Exam Preparation Kit

30 mins

A data-driven, all-module survival guide built from analyzing 75+ questions across 2022–2024 exam papers. Contains the guaranteed questions, the exact mark distribution, the 72-hour study plan, and the critical mistakes that fail students in Algorithms.

Learning Goals

Understand the exact module-wise mark distribution and identify the highest-ROI modules.
Know the 8 guaranteed question types that appear every single year.
Follow the 72-hour, 7-day, and 14-day study plans matched to your available preparation time.
Avoid the 10 most common exam mistakes in complexity analysis and algorithm tracing.

The Exam Architecture: Understanding the Paper

Before studying a single topic, understand how the exam is built. Based on 2022–2024 paper analysis:

Paper Structure:

Total Marks: 70 marks (external exam)
Duration: 3 hours
Section A: 10 MCQs × 2 marks = 20 marks (compulsory)
Section B: 5 long-answer questions × 10 marks OR internal choices yielding 50 marks total. Often split into 7-mark sub-questions.

The Critical Implication: Section A (MCQs) is worth 20 marks — nearly 30% of the paper — and takes only 15–20 minutes. Getting MCQs wrong is the single biggest reason students fail who otherwise "knew the algorithms."

The Module Power Ranking: Where Your Marks Actually Come From

Based on 75+ questions across 2022–2024, here is the data-driven importance ranking:

Rank	Module	Total PYQ Marks	Guaranteed Q?	Priority
#1	Module 2: Fundamental Strategies	129M	✅ MCM, Knapsack, Backtracking	🔴 CRITICAL
#2	Module 3: Graph & Tree Algorithms	112M	✅ Dijkstra, BFS/DFS, MST	🔴 CRITICAL
#3	Module 1: Introduction	108M	✅ Master's Theorem, Substitution	🔴 CRITICAL
#4	Module 4: Tractable/Intractable	38M	✅ P/NP Definitions, Cook's Theorem	🟠 HIGH (Easiest marks)
#5	Module 5: Advanced Topics	30M	✅ Randomized Quick Sort	🟡 MEDIUM

The ROI calculation: If you only study Modules 1, 2, and 3 perfectly, you can answer questions worth the vast majority of the paper. However, Module 4 is the "hack" — it contains only 38 tracked marks, but they are the exact same theory questions every year. Do not skip Module 4.

The 8 Guaranteed Question Types (Appear EVERY Year)

These are questions that have appeared in almost every exam from 2022 to 2024. If you master these 8, you can comfortably pass the paper.

🔴 GUARANTEED #1: Matrix Chain Multiplication DP Trace (7–14 Marks)

Module 2 | Priority: Absolute Maximum

Given matrix dimensions, find the minimum operations and optimal parenthesization.

What to practice: Drawing the $m$ (cost) and $s$ (split) tables.
Watch out for: Miscalculating $P_{i-1} \times P_k \times P_j$ .

🔴 GUARANTEED #2: Shortest Path Trace (7 Marks)

Module 3 | Priority: Absolute Maximum

Trace Dijkstra's or Bellman-Ford algorithm on a graph.

What to practice: The tabular relaxation format for Dijkstra. For Bellman-Ford, explicitly showing $|V|-1$ passes.

🔴 GUARANTEED #3: Substitution Method Recurrence (7 Marks)

Module 1 | Priority: Absolute Maximum

Solve a recurrence like $T(n) = 3T(n/2) + n$ using substitution.

What to practice: Expanding to the $k$ -th step, finding the pattern, and summing the series correctly to the base case.

🔴 GUARANTEED #4: Master's Theorem Application (5–7 Marks)

Module 1 | Priority: Absolute Maximum

Solve 2-3 recurrences using Master's Theorem.

What to practice: Memorizing all 3 cases, especially checking the regularity condition for Case 3 ( $a f(n/b) \le c f(n)$ ).

🟠 GUARANTEED #5: P / NP / NP-Complete Definitions (7 Marks)

Module 4 | Priority: High

Define P, NP, NP-Complete, and NP-Hard, and draw their relationship.

What to practice: The exact wording (e.g., "verifiable in polynomial time" for NP), and the Euler diagram assuming $P \neq NP$ .

🟠 GUARANTEED #6: Fractional Knapsack or Huffman Trace (7 Marks)

Module 2 | Priority: High

Solve fractional knapsack or generate Huffman codes.

What to practice: Always sorting by $Profit / Weight$ ratio first for Knapsack.

🟠 GUARANTEED #7: BFS vs DFS Comparison (7 Marks)

Module 3 | Priority: High

Compare BFS and DFS in terms of data structures, complexity, and applications.

What to practice: Memorizing the table: Queue vs Stack, Shortest Path vs Topological Sort.

🟡 GUARANTEED #8: Cook's Theorem & Reductions (7 Marks)

Module 4 | Priority: Medium

Explain Cook's Theorem and how to prove NP-Completeness via reduction.

What to practice: The 3-SAT to Vertex Cover reduction trace.

The 10 Most Common Exam Mistakes

These mistakes cost students 2–7 marks each and are entirely avoidable:

#	Mistake	Where	Marks Lost	Fix
1	Applying Master's Theorem when it fails	Module 1	2-3M	Watch out for $T(n) = 2T(n/2) + n/\log n$ . Master's Theorem DOES NOT apply here.
2	Skipping the regularity check in Case 3	Module 1	2M	If Case 3 of Master's applies, you MUST explicitly write $a f(n/b) \le c f(n)$ .
3	Using Greedy for 0/1 Knapsack	Module 2	7M	Greedy only works for Fractional Knapsack. 0/1 Knapsack requires DP.
4	Forgetting parent nodes in Dijkstra	Module 3	3M	Don't just write distances. Write `10 (A)` to show how you got there.
5	Bellman-Ford pass count error	Module 3	4M	You must show exactly $
6	Misparenthesizing MCM result	Module 2	2M	Tracing the table perfectly but writing $(A(BC)D)$ instead of $(A(BC))(D)$ .
7	Confusing NP-Hard and NP-Complete	Module 4	2M	NP-Complete must be IN NP. NP-Hard does not have to be in NP.
8	Confusing Backtracking and Branch & Bound	Module 2	3M	Backtracking finds all solutions (DFS). B&B finds the optimal solution (BFS/Priority Queue).
9	Not drawing the state-space tree	Module 2	4M	For N-Queens or Graph Coloring, the tree diagram IS the answer.
10	Confusing Las Vegas and Monte Carlo	Module 5	2M	Las Vegas = time varies, answer correct. Monte Carlo = time fixed, answer might be wrong.

The Study Plans: 72 Hours, 7 Days, and 14 Days

🔴 THE 72-HOUR EMERGENCY PLAN (3 Days Before Exam)

Goal: Pass (35/70 marks). Focus ONLY on guaranteed numericals and easy theory.

Day	Hours	What to Study
Day 1 (8hr)	4hr	Module 1: Master's Theorem (all 3 cases) + Substitution Method traces.
	4hr	Module 4: Memorize P/NP/NPC definitions, diagram, and Cook's Theorem.
Day 2 (8hr)	4hr	Module 3: Trace Dijkstra's and Bellman-Ford 3 times each on paper.
	4hr	Module 3: Memorize BFS vs DFS, Prim's vs Kruskal's theory tables.
Day 3 (4hr)	2hr	Module 2: Practice Fractional Knapsack and Huffman Coding.
	2hr	Revise all PYQ MCQs. Do NOT attempt Matrix Chain Multiplication (too risky to learn in 1 hour).

Expected score: 40–55 marks. You will pass.

🟡 THE 7-DAY PLAN (One Week Before Exam)

Goal: Score well (50–60/70 marks).

Day	Focus Module	Topics
Day 1	Module 1	Asymptotic notations, Substitution method, Master's Theorem.
Day 2	Module 2	Fractional Knapsack, Huffman, Compare DP/Greedy/D&C.
Day 3	Module 2	Matrix Chain Multiplication DP (spend the whole day tracing this).
Day 4	Module 3	Dijkstra, Bellman-Ford, Floyd-Warshall.
Day 5	Module 3	BFS, DFS, Prim's, Kruskal's, Topological Sort.
Day 6	Mod 4 & 5	P/NP definitions, reductions, Randomized Quick Sort.
Day 7	Revision	Redo all 2022–2024 MCQs. Practice 1 MCM and 1 Dijkstra trace.

🟢 THE 14-DAY MASTERY PLAN (Two Weeks Before Exam)

Goal: Score 65+ marks. Follow the 7-day plan, but allocate 2 full days to Module 2 (adding N-Queens, Graph Coloring, TSP), 2 full days to Module 3 (adding Ford-Fulkerson Max Flow), and take 2 full 3-hour mock exams using the 2023 and 2024 papers.

Quick-Reference: The 15 Definitions You MUST Memorize

#	Term	One-Line Definition
1	Big-O (O)	Asymptotic upper bound (worst-case scenario).
2	Big-Omega (Ω)	Asymptotic lower bound (best-case scenario).
3	Big-Theta (Θ)	Asymptotic tight bound (average/exact case).
4	Dynamic Programming	Solves optimization problems by breaking them into overlapping subproblems and storing results (memoization/tabulation).
5	Greedy Method	Makes the locally optimal choice at each step with the hope of finding the global optimum.
6	Backtracking	Explores all possible solutions via DFS, abandoning a path (pruning) as soon as it violates constraints.
7	Branch and Bound	Explores solutions to find the optimal one, pruning branches whose lower bound is worse than the best known solution.
8	Minimum Spanning Tree	A subset of edges in a weighted undirected graph that connects all vertices without cycles, with minimum total edge weight.
9	Topological Sort	A linear ordering of vertices in a DAG such that for every directed edge U→V, vertex U comes before V.
10	P Class	Decision problems solvable in polynomial time by a deterministic Turing machine.
11	NP Class	Decision problems whose solutions can be verified in polynomial time.
12	NP-Hard	Problems to which every problem in NP can be reduced in polynomial time.
13	NP-Complete	Problems that are BOTH in NP and are NP-Hard.
14	Cook's Theorem	States that the Boolean Satisfiability Problem (SAT) is NP-Complete.
15	Las Vegas Algorithm	A randomized algorithm that always gives the correct answer, but its runtime varies.

Formula Sheet: The Survival Equations

Master's Theorem: $T(n) = aT(n/b) + f(n)$

If $f(n) = O(n^{\log_b a - \epsilon})$ , then $T(n) = \Theta(n^{\log_b a})$
If $f(n) = \Theta(n^{\log_b a})$ , then $T(n) = \Theta(n^{\log_b a} \log n)$
If $f(n) = \Omega(n^{\log_b a + \epsilon})$ AND $af(n/b) \le cf(n)$ , then $T(n) = \Theta(f(n))$

Matrix Chain Multiplication: $m[i, j] = \min_{i \le k < j} \{ m[i, k] + m[k+1, j] + P_{i-1} P_k P_j \}$

Algorithm Time Complexities:

Binary Search: $O(\log n)$
Merge Sort / Quick Sort (Avg): $O(n \log n)$
BFS / DFS: $O(V + E)$
Dijkstra's: $O(E \log V)$ (with Min-Heap)
Bellman-Ford: $O(V \times E)$
Floyd-Warshall: $O(V^3)$
Prim's / Kruskal's: $O(E \log V)$

Knowledge Check

Question 1 of 2

Q1Single choice

You have exactly 3 hours before the DAA exam. Which numerical traces MUST you practice on paper to guarantee passing?

N-Queens and TSP Branch & Bound

Substitution Method, Dijkstra's Algorithm, and Master's Theorem

Ford-Fulkerson and KMP String Matching

Randomized Quick Sort and Vertex Cover Approximation

PYQDeck — Practice All DAA PYQs

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PYQ Analysis & Exam Preparation — Module 5