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Learn Trapping Rain Water, Top K Frequent and Selection Sort with Step-by-Step Visualization in DSA View View ๐Ÿ‘€๐Ÿ‘€

DSA View visualizes classic algorithms, aiding learning and debugging of data structures.

Steady
Signal score
18
Trajectory
โ†“ Cooling
7-day est. ~0

Why this scored 18

every term, weighted
Velocity+0.0 / 40

Engagement gained per hour since the last capture, against the fastest item on its own source

Acceleration+10.9 / 25

Whether that velocity is itself speeding up, as a per-hour rate

Cross-source spread+0.0 / 25

How many independent communities are talking about the same entity

Recency+8.5 / 10

Decays to zero over 14 days

Saturation penaltyโˆ’1.7 / 30

Subtracted once something is big and old โ€” we rank what's next, not what's peaked

Composite17.6

Weights are hand-tuned, not learned โ€” we're calibrating them against realized trends as history accumulates. On a topic's first sighting there's no previous reading to compare against, so acceleration starts from a neutral prior rather than a measurement, and velocity falls back to engagement over its whole lifetime until a second reading exists. Full methodology

Outlook

low confidence ยท estimate, not a guarantee

7-day

~0

range 0โ€“12

14-day

~0

range 0โ€“14

30-day

~0

range 0โ€“19

Signal history

7-day window (free)
071

projected trajectory (estimate, not a guarantee)

Entities

dsa view
Embed a live signal badge
Signalcrest signal badge
[![Signalcrest signal](https://www.signalcrest.app/api/badge/dev%3A4585958)](https://www.signalcrest.app/topic/dev%3A4585958)

Drop this in a README or blog post โ€” it updates automatically as the score moves.