single source shortest path practice question

Duration: 4 min

This video lesson is available to enrolled students.

Return to /learn/IBPS-SO-IT-PRELIMS/algorithms/shortest-path-algos/bellman-ford-algo/asset-single-source-shortest-path-practice-question after enrolling

Inside: a video lesson and guided study material.

Module outline

  1. About Course: About the Course
  2. English Language: Vocabulary, Noun, Adjectives, Tenses, Pronoun, Adverb, Preposition, Conjunction, Active Passive Voice (Voice), Articles, Direct and Indirect Speech, Sentence Correction (Error Correction), Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Sentence Completion (Fill in the blanks), Cloze Test (Cloze Passage)
  3. Reasoning: Series (Number and Letter Series) (Numerical Relations and Reasoning), Coding Decoding, Data Sufficiency, Puzzle Solving (Puzzles), Seating Arrangements, Blood Relations, Syllogisms, Inequality, Directions (Direction Test), Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Clock, Calendar, Analytical Reasoning (Counting Figures Reasoning), Selection Decision Table (Decision Making), Cubes & Dices, Machine Input-Output
  4. Quantitative Aptitude: Ratio and Proportion (Ratios), Data Interpretation, Mixture and Alligation, Permutation and Combination, Number System, Sequence and Series (Series), Speed Time and Distance, Algebra, Speed Mathematics and Basic Mathematics, Percentage, Average, Time and Work, Simple Interest and Compound Interest, Profit and Loss, Age Problems, Partnership, Mensuration and Geometry, Probability, IBPS Specific Videos
  5. Data Structures - Professional Knowledge: Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  6. Algorithms- Professional Knowledge: Algorithm Analysis, Time Complexity Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos
  7. Python- Professional Knowledge: Python for Placements by Yash Sir, Python Basics
  8. Operating System- Professional Knowledge: Introduction to OS, Process Management, CPU Scheduling, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management
  9. DBMS + SQL- Professional Knowledge: Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), File Organization & Indexing, SQL, Transaction Management, Concurrency Control
  10. Computer Networks- Professional Knowledge: Introduction to CN, Data Communication, Net Layer: IP Addressing, Net Layer: IPv4 & Proto, Application Layer, Hardware basics, Network Security
  11. Software Engineering- Professional Knowledge: Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  12. Computer Organization & Microprocessor- Professional Knowledge: Basics of COA, Cache Memory Organization, Programming the Basic Computer
  13. Digital Logic Design- Professional Knowledge: Digital Systems & Boolean Basics, Logic Gates & Hardware, Boolean Expression, Boolean Minimization, Combinational Circuit, Sequential Circuits, Number System, Number Representation
  14. Theory of Computation- Professional Knowledge: Introduction to TOC, Deterministic FA (DFA), Non-Deterministic FA, Regular Expressions, Regular Language Properties, Pushdown Automata & CFG, Turing Machines
  15. Compiler Design- Professional Knowledge: Intro to Compilers, Lexical Analysis, Grammar & CFG, Syntax Analysis: Top-Down, Intermediate Code Gen, Code Optimization
  16. Programming Languages- Professional Knowledge: C Programming by Yash Sir, Object Oriented Programming (OOPS), Programming in C++, Java, C Language Core
  17. Emerging Tech- Professional Knowledge: Emerging Tech Trends
  18. Artificial Intelligence: Artificial Intelligence
  19. Unit Test - Professional Knowledge:
  20. Full Length Mock Test:
AI summary & chapters

AI Summary

An AI-generated summary of this video lecture.

The video addresses a theoretical question in graph theory concerning the stability of shortest paths under uniform weight modification. The instructor begins by presenting the problem statement displayed on the screen: "If we increase weight of every edge by 1, the shortest path always remains same." He asks if this statement is true or false. To investigate this, he constructs a counterexample on the whiteboard. He writes "ex." and draws a graph with a source node 'S' on the left and a destination node 't' on the right. He creates two distinct paths between them. The first path, S -> A -> B -> C -> D -> t, consists of 5 edges with weights 2, 4, 5, 6, and 7 respectively, drawn in the upper section. The second path, S -> E -> t, consists of 2 edges with weights 10 and 15, drawn in the lower section.

Initially, the total weight of the first path is calculated as 2 + 4 + 5 + 6 + 7 = 24. The total weight of the second path is 10 + 15 = 25. Since 24 is less than 25, the first path is the shortest path. The instructor then applies the condition of the problem: increasing every edge weight by 1. The new weights for the first path become 3, 5, 6, 7, and 8, summing to 29. The new weights for the second path become 11 and 16, summing to 27. Comparing the new totals, 27 is now less than 29. This demonstrates that the shortest path has shifted from the first path to the second path. Consequently, the instructor concludes that the statement is false, marking "No" as the correct answer. He circles the "No" option to emphasize the conclusion.

Chapters

  1. 0:00 – 2:00 00:00-02:00

    The instructor introduces the problem statement regarding shortest paths and edge weight modification. He begins drawing a graph with source 'S' and destination 't', creating a multi-edge path S->A->B->C->D->t and a two-edge path S->E->t. He writes down the initial weights for each edge: 2, 4, 5, 6, 7 for the first path and 10, 15 for the second.

  2. 2:00 – 4:21 02:00-04:21

    The instructor calculates the initial total weights (24 vs 25) to establish the baseline shortest path. He then applies the transformation of adding 1 to every edge weight. He writes the new weights (3, 5, 6, 7, 8 and 11, 16) and calculates the new totals (29 vs 27). He demonstrates that the path with fewer edges becomes shorter, proving the statement false and selecting option (B) No.

The lesson demonstrates a critical property of shortest path algorithms: they are sensitive to uniform weight shifts if paths have different numbers of edges. By adding a constant to every edge, paths with more edges accumulate a larger total increase than paths with fewer edges. This example highlights that shortest paths are not invariant under such transformations, a key concept for understanding algorithm behavior in weighted graphs.

Loading lesson…