Automation framework design, tool depth, the SDET coding round, and CI integration.
Treat it as a process gap, not a grudge. Find out where and when decisions are made, get your team's constraints in front of the deciders before the meeting through short written proposals with a comment window both time zones can reach, and escalate a specific costly decision, not the people who made it.
Bitmask DP keeps the cheapest cost for every subset of workers already used. The number of set bits says which task comes next, so there are 2^n states with n moves each, O(2^n * n) time and 2^n memory. At n = 20 that is about a million states, where trying all 20! orders is hopeless.
Plain Dijkstra minimises cost alone, so it can return a cheap route with too many stops, and settling each city once discards a dearer route that still has stops to spare. Make the state city plus edges used, or run Bellman-Ford for exactly K + 1 rounds, each reading only the previous round's distances.
For one grid, number of islands is a flood fill: each unvisited land cell starts a BFS or DFS, O(rows x cols). For land arriving cell by cell, rerunning that is too slow, so use union-find. Each new cell adds one island, and each union with a neighbour in a different set removes one, at near-constant amortised cost.
Debugging an unfamiliar codebase starts by running the failing test, then reading it as the rule and tracing its call path to the code that computes the wrong value. Let the size of the error narrow the cause, ask the assistant to locate and explain rather than patch, and prove the fix with a test that failed before.
Binary search for the rotation point by comparing the middle element with the right end. If it is larger, the break lies to the right; otherwise it is at mid or before it. That is O(log n). With duplicates an equal comparison says nothing, so you drop the right end, and the worst case becomes O(n).