Data Structures and Algorithms in Python | 43. Longest common subsequence - Part A by Abraham | Learn Smarter
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Academics

Grades

Grade 8 Grade 9 Grade 10 Grade 11 Grade 12

Curriculum

CBSE ICSE IB
Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Professional Courses
Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

games
Typing
Memory
Math
English Adventures
Knowledge
43. Longest common subsequence - Part A

The chapter discusses the Longest Common Subsequence (LCS) problem, emphasizing the significance of understanding inductive and recursive structures in programming. It details methods for calculating LCS efficiently using dynamic programming, comparing it to brute force methods along with practical applications in genetics and file comparison. The recursive structure of the problem is outlined, illustrating how to derive solutions from simpler subproblems.

Sections

  • 43.1

    Longest Common Subsequence

    This section discusses the concepts of Longest Common Subsequence (LCS) through inductive definitions and dynamic programming techniques.

    Learning Practice

  • 43.1.1

    Inductive Definitions, Recursive Functions And Efficient Evaluation

    This section discusses inductive definitions and recursive functions in the context of dynamic programming, particularly focusing on the longest common subsequence problem.

    Learning Practice

  • 43.1.2

    Problem Description

    This section introduces the Longest Common Subsequence (LCS) problem, highlighting its significance in computer science and its inductive structure.

    Learning Practice

  • 43.1.3

    Brute Force Algorithm

    The section discusses the brute force algorithm to find the longest common subword between two strings, emphasizing the identification of inductive and recursive structures.

    Learning Practice

  • 43.1.4

    Inductive Structure

    This section discusses the inductive structure related to recursive functions and dynamic programming, particularly focusing on finding the longest common subsequence.

    Learning Practice

  • 43.1.5

    Computational Efficiency

    This section discusses the importance of computational efficiency in algorithms, focusing on the longest common subsequence problem and its dynamic programming approach.

    Learning Practice

  • 43.1.6

    Examples Of Using Longest Common Subsequence

    The section discusses the concept of Longest Common Subsequence (LCS) through examples and emphasizes inductive and recursive programming approaches.

    Learning Practice

  • 43.1.7

    Motivation For Longest Common Subsequence Problem

    This section discusses the importance of the Longest Common Subsequence (LCS) problem in computer science, particularly in areas like genetics and version control systems.

    Learning Practice

  • 43.1.8

    Inductive Structure Explanation

    This section explores the concept of inductive structures and their critical role in defining recursive functions for dynamic programming.

    Learning Practice

References

Chapter 43 part-A.pdf

Class Notes

Memorization

What we have learnt

  • Dynamic programming can sig...
  • Recognizing the inductive s...
  • The longest common subseque...

Final Test

Revision Tests