Google Big Code
In a distributed computing system, you are managing N memory cache blocks, each with a frequency level represented in an array A, along with an integer K. Cache blocks with the same frequency level are grouped together and can trigger recursive amplification cycles.
There exists exactly one shared, mutable global pool that tracks the count of cache blocks at each frequency level. It is initialized from array A. All operations read from blocks at each frequency level. It is initialized from array A. All operations read from this single pool. There are no snapshots, resets, or independent copies at any point during execution. All frequency counts in the pool fit within 64-bit signed integers throughout execution.
An amplification operation may be performed on frequency level X if the pool currently contains at least K cache blocks of level X. The operation proceeds as follows:
A chain is attempted for frequency level X only if X was present in the original input array A and count[X] ≥ K at the moment X is processed.
Complete the solve function. It receives N (the number of crystals), K (the number of crystals needed for transmutation), and A (an array of N integers representing crystal energy levels). The function uses hash table frequency tracking combined with greedy simulation to find the maximum score achievable through optimal transmutation chains. It returns the maximum total score as a long long.
N: integer — the number of crystals K: integer — the number of crystals required for each transmutation A: array of N long long integers — the energy levels of the crystals