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Course Detail

Course Name Competitive Programming
Course Code 26CSA303
Program 5 Year Integrated B.C.A – M.C.A
Semester 5
Credits 2
Campus Mysuru

Syllabus

Introduction to competitive programming and online judges, Input/output optimization and constraints handling

Implementation of basic problem‑solving patterns, Searching problems (binary search applications), Simple sorting‑based problems, Mathematical and number‑theory basics, Greedy strategy problems, Recursion and backtracking problems, Divide and conquer problem solving, Two‑pointer and sliding window techniques, Basic dynamic programming problems, String‑processing challenges, Timed contest / mock competition, Problem discussion and optimization techniques

Objectives and Outcomes

Course Objective(s) 

  • Develop strong algorithmic problem‑solving skills through continuous practice. 
  • Apply efficient algorithms and data structures for solving time‑constrained problems. 
  • Enhance the ability to analyze problem constraints and select optimal solutions. 
  • Familiarize students with online competitive programming platforms and tools. 

Course Outcomes 

COs 

Description 

CO1 

Analyze problem statements to identify constraints and suitable algorithmic strategies 

CO2 

Design efficient algorithms for computational problems under time and space constraints 

CO3 

Implement optimized solutions using appropriate programming languages and techniques 

CO4 

Evaluate solution efficiency and correctness by testing against diverse input cases 

CO5 

Demonstrate independent learning and adaptability by solving progressively complex problems 

CO-PO Mapping 

PO 

PO1 

PO2 

PO3 

PO4 

PO5 

PO6 

PO7 

PO8 

CO 

CO1 

3 

3 

2 

2 

0 

0 

0 

1 

CO2 

2 

3 

3 

2 

0 

0 

0 

1 

CO3 

3 

2 

3 

2 

0 

0 

0 

1 

CO4 

2 

3 

2 

2 

0 

0 

0 

1 

CO5 

2 

1 

2 

2 

0 

0 

0 

3 

Textbooks

  • Competitive Programming 4, Volumes 1 & 2, Competitive Programming Community, 2020 by Steven Halim and Felix Halim.
  • Guide to Competitive Programming: Learning and Improving Algorithms Through Contests, by Antti Laaksonen. Springer, 2017.

Evaluation Pattern

Assessment Weightage (%)
Continuous Assessment 70
End Semester Exam 30
Total Marks 100

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