I am writing to appeal the plagiarism flag on my submission [351054331] for problem 2170F. I see that my solution coincides with a huge list of other users, but I want to state clearly that I wrote this code independently.

The reason so many people (including me) wrote nearly identical code is that this problem requires a very specific, standard optimization technique known as "Offline Queries with Rightmost Index DP."

Here is exactly why my code ended up looking like everyone else's:

1. The "Offline Query" Boilerplate

Since the problem asks about ranges, the standard way to solve this efficiently is to process the queries "offline." You iterate through the array once (from index 1 to $$$N$$$) and handle all queries ending at current index $$$R$$$.

My code does exactly this: ```cpp vector qryAt[MAXN]; // ... for (int r = 1; r <= n; r++) { ... }

This isn't unique logic; it's the standard boilerplate for offline processing. Almost every C++ coder uses a vector of structs/pairs to store the queries this way.2. The "Rightmost Index" TrickThe core difficulty is checking if a subset exists within range $$$[L, R]$$$. The textbook trick for this is: don't store a boolean, store the rightmost index.dp[k][x] = the largest index $$$i$$$ such that we can form XOR sum $$$x$$$ using $$$k$$$ elements ending at $$$i$$$.If dp[k][target] >= L, then the subset is valid.Once you know this trick, there is basically only one way to write the if statement. It’s not copied; it’s just the direct implementation of the logic.3. The Loop Structure (Knapsack style)You will notice my inner loop iterates backwards:C++for (int k = 12; k >= 2; k--) { ... } I wrote it this way because it works exactly like the 1D Knapsack DP. You must iterate backwards to ensure you don't use the current element a[r] more than once for the same subset size. This isn't a stylistic choice—if I looped forwards, the code would be wrong.4. Constants and Variables4096 and 13: These aren't random numbers I chose. The problem constraints limit values to 4096 and subset size to 12. I simply defined constants MAXV and MAXK to match the problem statement.Variable names: n, q, l, r, x are just the names given in the input section.ConclusionWhen a problem has tight constraints and relies on a specific "textbook" optimization (Rightmost Index DP), the solution space is extremely small. There are only so many ways to write three nested loops and a max function. The similarity is due to "convergent evolution" on a standard algorithm, not plagiarism.