Solution #cfe29333-54b2-4967-b681-c147077458e0

failed

Score

0% (0/5)

Runtime

1.59ms

Delta

-100.0% vs parent

-100.0% vs best

Regression from parent

Solution Lineage

Current0%Regression from parent
4a986ae220%Regression from parent
7394353e56%Improved from parent
543fe3cf41%Improved from parent
43c9acdc20%Regression from parent
e4376bef41%Improved from parent
22df6ea426%Regression from parent
d36b2c9441%Improved from parent
a719a6aa19%Regression from parent
3d4a920597%Improved from parent
f1c258430%Regression from parent
05321f7320%Regression from parent
69815a2320%Improved from parent
f3a4c5bd20%Improved from parent
1734c2970%Same as parent
4f69822f0%Regression from parent
14d0b3da20%Improved from parent
528f38cd10%Regression from parent
0d6c341619%Regression from parent
ae69dbab39%Regression from parent
5a97585772%Improved from parent
5266c9ec0%Regression from parent
da617b596%Regression from parent
06ed21e748%Improved from parent
b618404727%Regression from parent
35f1acec41%Regression from parent
aacb270845%Improved from parent
44170f1439%Improved from parent
d4a144706%Regression from parent
ac75ae0340%Regression from parent
5d1898f963%Improved from parent
669949f251%Regression from parent
cdf35bb558%Improved from parent
1c6ceef237%Regression from parent
a48275e057%Improved from parent
b6016c2857%Improved from parent
5fad927440%Regression from parent
cb4d87e147%Improved from parent
7f265cec45%Improved from parent
2143671f19%Improved from parent
c0d68d5c0%Regression from parent
ae54b0ca54%Regression from parent
e0f66b5554%Improved from parent
465e93a245%Regression from parent
73be1f5e49%Improved from parent
dd5155da19%Improved from parent
a9d69e700%Regression from parent
63acaad058%Improved from parent
1265a3fc48%Improved from parent
693a4dda33%Regression from parent
d5bf925948%Regression from parent
48e560c749%Improved from parent
78afbd2538%Improved from parent
f0098ec50%Same as parent
bb8caee80%Regression from parent
ce53db5152%Improved from parent
9e6f727542%Improved from parent
2c6b742934%Regression from parent
223a455254%Improved from parent
4a54e07352%Improved from parent
99326a1432%Improved from parent
d8629f4919%Regression from parent
0deb287347%Improved from parent
e4b007c347%Improved from parent
32b7128c43%Regression from parent
f209f80655%Improved from parent
9161b31714%Regression from parent
9ab0f66324%Improved from parent
110fbd0b0%Regression from parent
e3d01a5c52%Improved from parent
c6fc252643%Regression from parent
23b4491152%Improved from parent
03aea6db43%Regression from parent
5f1a15ce53%Improved from parent
f22b171153%Same as parent
7b6d9f0953%Improved from parent
0401f74f12%Regression from parent
b96fbcb340%Improved from parent
84cc9d0420%First in chain

Code

def solve(input):
    data = input.get("data", "")
    if not isinstance(data, str) or not data:
        return 999.0
    
    # Implement a simple dictionary-based compression (LZ77 variant)
    def lz77_compress(text):
        # Initialize window and buffer sizes
        window_size = 256
        buffer_size = 15
        
        compressed = []
        i = 0
        while i < len(text):
            match_length = 0
            match_distance = 0
            # Look for the longest match in the sliding window
            for j in range(max(0, i - window_size), i):
                k = 0
                while k < buffer_size and i + k < len(text) and text[j + k] == text[i + k]:
                    k += 1
                if k > match_length:
                    match_length = k
                    match_distance = i - j
            
            if match_length >= 3:  # If match is found and is worthwhile
                compressed.append((match_distance, match_length, text[i + match_length] if i + match_length < len(text) else ''))
                i += match_length + 1
            else:
                compressed.append((0, 0, text[i]))
                i += 1
        
        return compressed

    def lz77_decompress(compressed):
        decompressed = []
        for distance, length, next_char in compressed:
            if length > 0:
                start_index = len(decompressed) - distance
                decompressed.extend(decompressed[start_index:start_index + length])
            if next_char:
                decompressed.append(next_char)
        return ''.join(decompressed)

    # Compress and Decompress
    compressed_data = lz77_compress(data)
    decompressed_data = lz77_decompress(compressed_data)

    if decompressed_data != data:
        return 999.0

    original_size = len(data) * 8
    compressed_size = sum(8 + 8 + 8 for _, _, next_char in compressed_data if next_char) + sum(8 + 8 for _, length, _ in compressed_data if length > 0)

    if original_size == 0:
        return 999.0

    compression_ratio = compressed_size / original_size
    return 1.0 - compression_ratio