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DSA Cprogramming~10 mins

Minimum Spanning Tree Kruskal's Algorithm in DSA C - Execution Trace

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Concept Flow - Minimum Spanning Tree Kruskal's Algorithm
Start with all edges sorted by weight
Pick smallest edge
Check if adding edge forms cycle?
Add edge to MST
Are all vertices connected?
Done
Kruskal's algorithm sorts edges by weight, then adds edges one by one to the MST if they don't form a cycle, until all vertices are connected.
Execution Sample
DSA C
Edges = [(A-B,1), (B-C,3), (A-C,2), (C-D,4)]
Sort edges by weight
Initialize MST = {}
For each edge in sorted order:
  If edge does not form cycle:
    Add edge to MST
Return MST
This code builds a minimum spanning tree by adding edges from smallest to largest weight without creating cycles.
Execution Table
StepOperationEdge ConsideredCycle Check ResultMST EdgesVisual State
1Sort edges by weight--{}No edges yet
2Consider edgeA-B (1)No cycle{A-B}A--B
3Consider edgeA-C (2)No cycle{A-B, A-C}A--B | C
4Consider edgeB-C (3)Forms cycle{A-B, A-C}A--B | C
5Consider edgeC-D (4)No cycle{A-B, A-C, C-D}A--B | C--D
6Check if MST complete-Yes{A-B, A-C, C-D}All vertices connected
7Done--{A-B, A-C, C-D}Final MST
💡 All vertices connected, MST complete with edges A-B, A-C, C-D
Variable Tracker
VariableStartAfter Step 2After Step 3After Step 4After Step 5Final
MST Edges{}{A-B}{A-B, A-C}{A-B, A-C}{A-B, A-C, C-D}{A-B, A-C, C-D}
Edges Considered[][A-B][A-B, A-C][A-B, A-C, B-C][A-B, A-C, B-C, C-D][A-B, A-C, B-C, C-D]
Connected Components4 (A,B,C,D separate)3 (A-B connected)2 (A-B-C connected)2 (no change, B-C edge discarded)1 (all connected)1 (all connected)
Key Moments - 3 Insights
Why do we discard the edge B-C (3) even though it connects two vertices?
Because adding edge B-C would create a cycle with edges A-B and A-C already in MST, as shown in step 4 of the execution_table where cycle check result is 'Forms cycle'.
How do we know when the MST is complete?
When all vertices are connected in a single component, meaning the number of connected components is 1, as shown after step 5 in variable_tracker and confirmed in step 6 of execution_table.
Why do we sort edges by weight at the start?
Sorting ensures we always pick the smallest edge first to build the MST with minimum total weight, as shown in step 1 of execution_table.
Visual Quiz - 3 Questions
Test your understanding
Look at the execution_table at step 4, what is the cycle check result for edge B-C (3)?
ANo cycle
BForms cycle
CEdge not considered
DEdge added to MST
💡 Hint
Check the 'Cycle Check Result' column at step 4 in execution_table
At which step does the MST become complete with all vertices connected?
AStep 6
BStep 5
CStep 3
DStep 7
💡 Hint
Look at the 'Check if MST complete' operation and connected components in variable_tracker
If the edge C-D (4) was removed from the graph, what would happen to the MST?
AMST would have fewer edges but still connect all vertices
BMST would include edge B-C (3) instead
CMST would be incomplete, some vertices disconnected
DNo change, MST remains the same
💡 Hint
Refer to the visual state and connected components after step 5 in variable_tracker
Concept Snapshot
Kruskal's Algorithm builds MST by:
- Sorting edges by weight
- Adding edges from smallest to largest
- Skipping edges that form cycles
- Stopping when all vertices connect
Uses Union-Find or similar to detect cycles
Full Transcript
Kruskal's algorithm starts by sorting all edges by their weight. It then picks the smallest edge and checks if adding it creates a cycle in the growing MST. If no cycle forms, the edge is added. If a cycle would form, the edge is discarded. This process repeats until all vertices are connected in one component, forming the minimum spanning tree. The execution table shows each step with edges considered, cycle checks, and the MST's state. The variable tracker follows MST edges and connected components count. Key moments clarify why edges causing cycles are skipped and how completion is detected. The visual quiz tests understanding of cycle detection, MST completion, and effects of missing edges.