Build fluency in the vocabulary of connecting every node in a graph at the lowest possible total edge weight.
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At standup, a dev mentions selecting a subset of a graph's edges that connects every node together, contains no cycles, and has the smallest possible total edge weight among all such subsets. What is this structure called?
A minimum spanning tree is exactly this: a subset of a graph's edges that connects every node together, contains no cycles, and has the smallest possible total edge weight among every such subset. A hash collision is an unrelated hash-table concept about two keys sharing a bucket. This lowest-total-weight, cycle-free, fully-connecting property is exactly why a minimum spanning tree is the standard answer for connecting every location in a network for the least total cost.
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During a design review, the team builds a minimum spanning tree specifically so a network of locations can all be connected using the least possible total cost of cabling or wiring. Which capability does this provide?
A minimum spanning tree here provides a cycle-free connection of every location at the minimum possible total edge cost, since any cycle in a connecting subset of edges would mean at least one of those edges is redundant and could be removed while every location stays connected, so a true minimum spanning tree never contains a cycle. Connecting every pair of locations directly would cost vastly more than the minimum needed just to keep the whole network connected. This lowest-total-cost, cycle-free guarantee is exactly why a minimum spanning tree is the standard structure for cost-efficient network design.
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In a code review, a dev notices a network-design feature connects every location by including every possible edge between them, rather than selecting only the subset of edges needed to keep everything connected at minimum cost. What does this represent?
This is a missed minimum-spanning-tree opportunity, since including every possible edge between locations pays for a huge number of redundant connections, when a minimum spanning tree would select only the cycle-free subset of edges needed to keep every location connected at the lowest possible total weight. A cache eviction policy is an unrelated concept about discarded cache entries. This include-every-edge pattern is exactly the kind of unnecessary cost a reviewer flags once only full connectivity, not every possible direct link, is actually required.
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An incident report shows a network build-out cost far more than budgeted, because the design connected every location by including every possible edge between them instead of selecting the minimum-cost subset needed to keep everything connected. What practice would prevent this?
Computing a minimum spanning tree over the candidate edges selects only the cycle-free subset needed to keep every location connected at the lowest possible total weight, which is exactly the fix for the budget overrun described in this incident. Continuing to include every possible edge between locations regardless of the redundant cost is exactly what drove the build-out over budget. This minimum-spanning-tree computation is the standard fix whenever a network design only needs full connectivity, not every possible direct link between every pair of locations.
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During a PR review, a teammate asks why the team computes a minimum spanning tree instead of just connecting each new location to its single nearest existing neighbor greedily, without considering the whole network's total cost. What is the reasoning?
A minimum spanning tree is computed by considering the whole network's edge weights together, guaranteeing the lowest possible total cost across the entire structure, while greedily connecting each new location only to its single nearest existing neighbor can still produce a fully connected network, just not necessarily the cheapest one overall. The tradeoff is that a true minimum-spanning-tree algorithm needs to examine and compare edges across the whole graph rather than making a purely local decision at each step. This is exactly why a proper minimum-spanning-tree algorithm, like the well-known greedy-with-global-bookkeeping approaches, is preferred whenever minimizing total network cost genuinely matters.
What does the "Minimum Spanning Tree Vocabulary" vocabulary exercise cover?
This exercise tests real IT vocabulary related to minimum spanning tree vocabulary through 5 multiple-choice questions, each built from realistic workplace sentences rather than abstract definitions.
Is this vocabulary exercise free to use?
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How many questions does this exercise have?
This exercise has 5 questions. Each one shows a real-world sentence or scenario with multiple-choice options and an explanation once you answer.
What happens after I answer a question?
You'll see immediate feedback showing whether your answer was correct, along with a short explanation of why — then a button to move to the next question, and a full results screen at the end.
Can I retry the exercise if I get questions wrong?
Yes. Once you reach the results screen, click "Try again" to reset your answers and go through the exercise from the start as many times as you like.
Do I need to create an account to take this exercise?
No account is needed. Your answers are scored in your browser during the session — nothing is saved to a server, so you can jump straight in.
Is my progress saved if I leave the page?
No — progress within an exercise resets if you navigate away or reload. Each exercise is short enough to complete in a few minutes in one sitting.
Are these vocabulary exercises connected to other topics?
Yes — browse the full vocabulary exercises hub to find related modules covering adjacent IT topics and roles.
How is this different from reading a glossary or blog article?
Exercises like this one are active recall drills — you have to choose the correct term or phrasing yourself, which builds retention faster than passively reading a definition.
Where can I find more vocabulary exercises?
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