AKTU Design and Analysis of Algorithm · Important Questions 2026Source: ryzenstudy.com PYQs
BCS503 Design and Analysis of Algorithm Important Questions 2026 (AKTU)
Repeat analysis + most-asked questions, unit-wise
What we did: built from all 5 AKTU Design and Analysis of Algorithm papers (2021-22–2025-26): 119 questions grouped into 73 distinct questions, 28 of which were asked in more than one paper.
- of marks were repeat questions
- 57%
- of marks were repeat questions
- questions asked in 2+ papers
- 28
- questions asked in 2+ papers
- papers analysed (2021-22–2025-26)
- 5
- papers analysed (2021-22–2025-26)
- units, mapped to current syllabus
- 5
- units, mapped to current syllabus
How much of the paper repeats?
- Repeats are real: when we checked each newer BCS503 paper against the papers before it, on average 57% of its marks were questions already asked in an earlier paper.
- 2023-24 paper: 53% of marks were repeats (6 of 10 repeated questions were in our top list).
- 2024-25 paper: 74% of marks were repeats (8 of 16 repeated questions were in our top list).
- 2025-26 paper: 43% of marks were repeats (4 of 9 repeated questions were in our top list).
- Topic weightage is a guide, not a guarantee: our Tier 1 + Tier 2 topics covered 58% of the next paper's marks — picking the same number of topics at random would have covered about 51%.
Across 10 subjects and 23 papers we tested, 43% of marks repeated earlier questions on average.
1.Unit-wise most-asked questions
Ranked by how many papers asked them, then by how recently. Click a paper to open it.
Unit 1: Introduction
25% of past marks| Question | Asked |
|---|---|
| Compute the time complexity of the following recurrence relation (see original paper) | Asked 3× |
| Explain Merge Sort with example and also compute time complexity | Asked 3× |
| Define algorithm and its characteristics | Asked 3× |
| Illustrate the operation of Merge Sort on array A = (38, 27, 43, 3, 9, 82, 10). Also derive the time complexity of Merge Sort | Asked 3× |
Unit 2: Advanced Data Structures
19% of past marks| Question | Asked |
|---|---|
| Insert the following elements using the property of RB tree (see original paper for the elements) | Asked 3× |
| Define Binomial Heap. Write an algorithm for union of two binomial heaps. Also take a suitable example which clearly illustrates merging operation of two binomial heaps | Asked 2× |
| Prove all the four properties of Binomial Tree | Asked 2× |
| Explain Fibonacci Heap with suitable example 7 marks2025-26 Q2(e) | Asked 1× |
Unit 3:
16% of past marks| Question | Asked |
|---|---|
| Explain Kruskal's algorithm for MST and also discuss the time complexity | Asked 4× |
| Explain Dijkstra's Algorithm. Prove that it may fail if the graph contains negative edge weights | Asked 4× |
| Find the optimal solution of the fractional Knapsack problem with n=7 and the knapsack capacity of m=15. The profits and weights of the items are given below. Objects: 1 2 3 4 5 6 7; Profit (P): 5 10 15 7 8 9 4; Weight (w): 1 3 5 4 1 3 2 | Asked 2× |
| With a suitable example explain the concept of Convex Hull Problem | Asked 2× |
Unit 4:
22% of past marks| Question | Asked |
|---|---|
| Explain the Branch and Bound approach for the Travelling Salesman Problem (TSP) using the "Reduced Cost Matrix" method | Asked 3× |
| Illustrate the N-queens problem? Draw "State Space Tree" for 4 queen's problem using backtracking | Asked 3× |
| Write Floyd's and Warshall's algorithm to find all pair shortest path in a graph. Discuss its time complexity | Asked 3× |
| Solve a 0/1 Knapsack problem with given profits [60, 100, 120, 90, 75, 45], weights [5, 10, 15, 20, 35, 40] and capacity = 50 using Dynamic Programming | Asked 2× |
Unit 5: Selected Topics
19% of past marks| Question | Asked |
|---|---|
| Write Knuth-Morris-Pratt string matching algorithm. Take a suitable example. Compute the prefix function for the pattern ababbabbabbababbabb when the alphabet is Sigma = {a, b} | Asked 3× |
| Describe "Randomized algorithms". List few randomized algorithms | Asked 3× |
| Describe the Boyer-Moore string matching algorithm. How do the "bad character" and "good suffix" heuristics work? | Asked 2× |
| Explain Vertex Cover Problem. Solve vertex cover problem using approximation algorithm | Asked 2× |
2.Topic weightage: which topics carry the marks
Blue = Tier 1 + Tier 2 (topics that carried ~80% of past marks). Grey = the rest. It shows where marks have gone, not a promise of what comes next.
Binomial heaps · U2
7.9% (cum 8%)
Merge sort · U1
6.4% (cum 14%)
Dynamic programming and optimality · U4
6.1% (cum 20%)
Minimum spanning trees · U3
6% (cum 26%)
Backtracking basics · U4
5.6% (cum 32%)
Single source shortest paths · U3
5.2% (cum 37%)
KMP and Boyer-Moore matching · U5
4.5% (cum 42%)
Naive and Rabin-Karp matching · U5
4.4% (cum 46%)
Recurrences and complexity analysis · U1
4.1% (cum 50%)
Red-black trees · U2
3.9% (cum 54%)
Branch and bound, TSP · U4
3.8% (cum 58%)
NP-completeness · U5
3.6% (cum 62%)
Knapsack and reliability allocation · U3
3.3% (cum 65%)
Asymptotic notation and growth · U1
3.3% (cum 68%)
Approximation algorithms · U5
3.1% (cum 71%)
Graph coloring and n-queens · U4
2.9% (cum 74%)
All pairs shortest paths · U4
2.9% (cum 77%)
Quick sort and Shell sort · U1
2.8% (cum 80%)
Randomized algorithms · U5
2.7% (cum 83%)
Algorithms and design steps · U1
2.7% (cum 85%)
Skip list · U2
2.6% (cum 88%)
Sorting in linear time · U1
2.1% (cum 90%)
Fibonacci heaps · U2
2.1% (cum 92%)
Heap sort · U1
1.6% (cum 94%)
Sorting comparison and stability · U1
1.6% (cum 95%)
B-trees · U2
1% (cum 96%)
Tries · U2
1% (cum 97%)
Divide and conquer, convex hull · U3
1% (cum 98%)
Greedy method basics · U3
0.8% (cum 99%)
Resource allocation problem · U4
0.5% (cum 99%)
Algebraic computation and FFT · U5
0.4% (cum 100%)
| Topic | Papers | Share |
|---|---|---|
| Binomial heaps · Unit 2 · Tier 1 | 4/5 | 7.9% |
| Merge sort · Unit 1 · Tier 1 | 5/5 | 6.4% |
| Dynamic programming and optimality · Unit 4 · Tier 1 | 4/5 | 6.1% |
| Minimum spanning trees · Unit 3 · Tier 1 | 5/5 | 6% |
| Backtracking basics · Unit 4 · Tier 1 | 5/5 | 5.6% |
| Single source shortest paths · Unit 3 · Tier 1 | 5/5 | 5.2% |
| KMP and Boyer-Moore matching · Unit 5 · Tier 1 | 4/5 | 4.5% |
| Naive and Rabin-Karp matching · Unit 5 · Tier 1 | 3/5 | 4.4% |
| Recurrences and complexity analysis · Unit 1 · Tier 1 | 3/5 | 4.1% |
| Red-black trees · Unit 2 · Tier 2 | 4/5 | 3.9% |
| Branch and bound, TSP · Unit 4 · Tier 2 | 4/5 | 3.8% |
| NP-completeness · Unit 5 · Tier 2 | 5/5 | 3.6% |
| Knapsack and reliability allocation · Unit 3 · Tier 2 | 4/5 | 3.3% |
| Asymptotic notation and growth · Unit 1 · Tier 2 | 3/5 | 3.3% |
| Approximation algorithms · Unit 5 · Tier 2 | 3/5 | 3.1% |
| Graph coloring and n-queens · Unit 4 · Tier 2 | 3/5 | 2.9% |
| All pairs shortest paths · Unit 4 · Tier 2 | 3/5 | 2.9% |
| Quick sort and Shell sort · Unit 1 · Tier 2 | 3/5 | 2.8% |
| Randomized algorithms · Unit 5 · Tier 2 | 4/5 | 2.7% |
| Algorithms and design steps · Unit 1 · Tier 3 | 4/5 | 2.7% |
| Skip list · Unit 2 · Tier 3 | 3/5 | 2.6% |
| Sorting in linear time · Unit 1 · Tier 3 | 2/5 | 2.1% |
| Fibonacci heaps · Unit 2 · Tier 3 | 3/5 | 2.1% |
| Heap sort · Unit 1 · Tier 3 | 2/5 | 1.6% |
| Sorting comparison and stability · Unit 1 · Tier 3 | 2/5 | 1.6% |
| B-trees · Unit 2 · Tier 3 | 1/5 | 1% |
| Tries · Unit 2 · Tier 3 | 1/5 | 1% |
| Divide and conquer, convex hull · Unit 3 · Tier 3 | 2/5 | 1% |
| Greedy method basics · Unit 3 · Tier 3 | 2/5 | 0.8% |
| Resource allocation problem · Unit 4 · Tier 3 | 1/5 | 0.5% |
| Algebraic computation and FFT · Unit 5 · Tier 3 | 1/5 | 0.4% |
3.Paper pattern (2025-26)
| Section | Questions | Rule |
|---|---|---|
| A | 7 × 2 marks | Attempt all |
| B | 5 × 7 marks | Attempt any 3 |
| C | 10 × 7 marks | Attempt any 1 |
4.In the syllabus, never asked yet
Low priority, but read them once — a new paper can always start here.
- Hamiltonian cycles, sum of subsets · U4
5.Study order
- 1Binomial heaps (Unit 2, Tier 1)
- 2Merge sort (Unit 1, Tier 1)
- 3Dynamic programming and optimality (Unit 4, Tier 1)
- 4Minimum spanning trees (Unit 3, Tier 1)
- 5Backtracking basics (Unit 4, Tier 1)
- 6Single source shortest paths (Unit 3, Tier 1)
- 7KMP and Boyer-Moore matching (Unit 5, Tier 1)
- 8Naive and Rabin-Karp matching (Unit 5, Tier 1)
- 9Recurrences and complexity analysis (Unit 1, Tier 1)
- 10Red-black trees (Unit 2, Tier 2)
- 11Branch and bound, TSP (Unit 4, Tier 2)
- 12NP-completeness (Unit 5, Tier 2)
- 13Knapsack and reliability allocation (Unit 3, Tier 2)
- 14Asymptotic notation and growth (Unit 1, Tier 2)
- 15Approximation algorithms (Unit 5, Tier 2)
- 16Graph coloring and n-queens (Unit 4, Tier 2)
- 17All pairs shortest paths (Unit 4, Tier 2)
- 18Quick sort and Shell sort (Unit 1, Tier 2)
- 19Randomized algorithms (Unit 5, Tier 2)
FAQ
Which units of BCS503 carry the most marks?
Unit 1 (Introduction, 25% of past marks) and Unit 4 (, 22% of past marks).
Do AKTU Design and Analysis of Algorithm questions repeat?
Yes. On average 57% of the marks in each newer BCS503 paper came from questions already asked in an earlier paper, and 28 questions have appeared in more than one paper.
How is this list made?
Every question from the 5 papers (2021-22–2025-26) was mapped to the current AKTU syllabus and grouped with the same question from other years. Questions are ranked by how many papers they appeared in, then by how recently.
Study this subject
Note: this is based on past AKTU papers, not a guarantee. Questions are mapped to the current syllabus; topics that are no longer in the syllabus are left out.