single source shortest path practice question

Duration: 4 min

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Module outline

  1. Quantitative Ability: Percentage, Profit and Loss, Ratio and Proportion (Ratios), Average, Time and Work, Speed Time and Distance, Simple Interest and Compound Interest, Age Problems, Number System, Divisibility Rules, HCF LCM, Algebra, Permutation and Combination, Probability, Data Interpretation, Logarithm, Sequence and Series (Series), Powers and Exponents (Surds and Indices), Speed Mathematics and Basic Mathematics
  2. Logical Reasoning: Seating Arrangements, Puzzle Solving (Puzzles), Data Arrangement, Coding Decoding, Blood Relations, Directions (Direction Test), Ranking, Order and Sequence, Data Sufficiency, Venn Diagram, Inequality, Series (Number and Letter Series) (Numerical Relations and Reasoning), Logical Sequence Of Words, Deductive and Inductive Reasoning (Logical Deduction and Induction) (Prepositional Reasoning), Selection Decision Table (Decision Making), Analogy, Non Verbal Reasoning (Spatial Aptitude) (Spatial Reasoning) (Visual Reasoning)
  3. Verbal Ability: Comprehension / Reading Comprehension / Unseen Passages (Critical Reasoning) (Paragraph Questions), Subject Verb Agreement (Verb Noun Agreement), Tenses, Articles, Preposition, Conjunction, Modals, Active Passive Voice (Voice), Direct and Indirect Speech, Vocabulary, Sentence Re-arrangements (Para Jumbles) (Narrative Sequencing), Sentence Completion (Fill in the blanks), Sentence Correction (Error Correction), Cloze Test (Cloze Passage), Facts, Inference and Judgements
  4. Programming Fundamentals (Technical): C Fundamentals
  5. Data Structures (Technical): Introduction to DS, Array, Stack, Queue, Linked List, Tree, Graphs, Hashing
  6. Algorithms (Technical): Algorithm Analysis, Sorting Algorithms, Greedy Algorithms, Dynamic Programming, Minimum Spanning Trees, Shortest Path Algos, Time Complexity Analysis, Advanced Algorithms
  7. OOPs (Technical): Object Oriented Programming (OOPS)
  8. DBMS (Technical): Basics of DBMS, ER Diagram, Relational Model & Functional Dependencies, Keys & Integrity Constraints, Normalization (1NF - BCNF), Decomposition Properties & 4NF, File Organization & Indexing, Relational Algebra, Relational Calculus, Transaction Management, Concurrency Control, Database Recovery, ORDBMS, Database Security & Authorization, Query Processing & Optimization, Enhanced Data Models, Data Warehousing & Mining, Big Data Systems, NoSQL
  9. SQL (Technical): SQL
  10. Operating Systems (Technical): Introduction to OS, Process Management, CPU Scheduling, Process Synchronization, Deadlock, Threads & Process Creation, Memory Management, Virtual Memory, Disc Scheduling, File Management, Windows OS, Linux OS, Security, Distributed Systems, Virtual Machines
  11. Computer Networks (Technical): Introduction to CN, Data Communication, DLL: Access Control, DLL: Flow Control, DLL: Error Control, DLL: Framing, Data Link Layer - Ethernet, Net Layer: IPv4 & Proto, Net Layer: IP Addressing, Net Layer:Routing Protocol, Transport Layer Services, TL: Congestion & UDP, Application Layer, Hardware basics, Network Security, Mobile Technology, Cloud Computing and IoT, Cyber and Info Security
  12. Software Engineering (Technical): Fundamentals of Software Engineering, Software Requirements and Quality Assurance, Software Design, Estimation and Metrics, Software Testing, Software Maintenance and Configuration Management
  13. Coding/Automata Round: Coding Questions by Yash Sir, C Programming by Yash Sir, Programming in C++, Java, Python for Placements by Yash Sir, Pseudo Codes
  14. Personality / Behavioral Assessment: Behavioral Assessment (Behavioral Competency Profiling) (Psychometric Test)
  15. Writing Assessment: English Writing Ability
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.

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