# File: optimal_game_value.py
 
def max_abs_sum_gain(a1, b1, a2, b2):
    # Computes the maximum possible gain in value from Bahamin's optimal swap
    orig = abs(a1 - b1) + abs(a2 - b2)
    values = [a1, b1, a2, b2]
    max_new = 0
    for x1 in values:
        for x2 in values:
            if x1 == x2: continue
            remaining = values[:]
            remaining.remove(x1)
            remaining.remove(x2)
            y1, y2 = remaining
            new_v = abs(x1 - y1) + abs(x2 - y2)
            max_new = max(max_new, new_v)
    return max_new - orig
 
def solve():
    import sys
    input = sys.stdin.read
    data = input().split()
 
    idx = 0
    t = int(data[idx]); idx += 1
    results = []
    for _ in range(t):
        n = int(data[idx]); idx += 1
        k = int(data[idx]); idx += 1
        a = list(map(int, data[idx:idx+n])); idx += n
        b = list(map(int, data[idx:idx+n])); idx += n
 
        initial_v = sum(abs(a[i] - b[i]) for i in range(n))
        gains = []
 
        # Try only i and i+1 to limit complexity (O(n))
        for i in range(n - 1):
            gain = max_abs_sum_gain(a[i], b[i], a[i+1], b[i+1])
            if gain > 0:
                gains.append(gain)
 
        # Sort and apply top k gains
        gains.sort(reverse=True)
        final_v = initial_v + sum(gains[:k])
        results.append(str(final_v))
 
    print("\n".join(results))
 
# Uncomment below if running directly:
# if __name__ == "__main__":
#     solve()

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

NQoyIDEKMSA3CjMgNQozIDIKMSA1IDMKNiAyIDQKNSA0CjEgMTYgMTAgMTAgMTYKMyAyIDIgMTUgMTUKNCAxCjIzIDEgMTggNAoxOSAyIDEwIDMKMTAgMTAKNCAzIDIgMTAwIDQgMSAyIDQgNSA1CjEgMjAwIDQgNSA2IDEgMTAgMiAzIDQK

5
2 1
1 7
3 5
3 2
1 5 3
6 2 4
5 4
1 16 10 10 16
3 2 2 15 15
4 1
23 1 18 4
19 2 10 3
10 10
4 3 2 100 4 1 2 4 5 5
1 200 4 5 6 1 10 2 3 4