RFC1951 - DEFLATE Compressed Data Format Specification version 1.3

Network Working Group P. Deutsch

Request for Comments: 1951 Aladdin Enterprises

Category: Informational May 1996

DEFLATE Compressed Data Format Specification version 1.3

Status of This Memo

This memo provides information for the Internet community. This memo

does not specify an Internet standard of any kind. Distribution of

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Abstract

This specification defines a lossless compressed data format that

compresses data using a combination of the LZ77 algorithm and Huffman

coding, with efficiency comparable to the best currently available

general-purpose compression methods. The data can be prodUCed or

consumed, even for an arbitrarily long sequentially presented input

data stream, using only an a priori bounded amount of intermediate

storage. The format can be implemented readily in a manner not

covered by patents.

Table of Contents

1. Introduction ................................................... 2

1.1. Purpose ................................................... 2

1.2. Intended audience ......................................... 3

1.3. Scope ..................................................... 3

1.4. Compliance ................................................ 3

1.5. Definitions of terms and conventions used ................ 3

1.6. Changes from previous versions ............................ 4

2. Compressed representation overview ............................. 4

3. Detailed specification ......................................... 5

3.1. Overall conventions ....................................... 5

3.1.1. Packing into bytes .................................. 5

3.2. Compressed block format ................................... 6

3.2.1. Synopsis of prefix and Huffman coding ............... 6

3.2.2. Use of Huffman coding in the "deflate" format ....... 7

3.2.3. Details of block format ............................. 9

3.2.4. Non-compressed blocks (BTYPE=00) ................... 11

3.2.5. Compressed blocks (length and distance codes) ...... 11

3.2.6. Compression with fixed Huffman codes (BTYPE=01) .... 12

3.2.7. Compression with dynamic Huffman codes (BTYPE=10) .. 13

3.3. Compliance ............................................... 14

4. Compression algorithm details ................................. 14

5. References .................................................... 16

6. Security Considerations ....................................... 16

7. Source code ................................................... 16

8. Acknowledgements .............................................. 16

9. Author's Address .............................................. 17

1. Introduction

1.1. Purpose

The purpose of this specification is to define a lossless

compressed data format that:

* Is independent of CPU type, operating system, file system,

and character set, and hence can be used for interchange;

* Can be produced or consumed, even for an arbitrarily long

sequentially presented input data stream, using only an a

priori bounded amount of intermediate storage, and hence

can be used in data communications or similar structures

such as Unix filters;

* Compresses data with efficiency comparable to the best

currently available general-purpose compression methods,

and in particular considerably better than the "compress"

program;

* Can be implemented readily in a manner not covered by

patents, and hence can be practiced freely;

* Is compatible with the file format produced by the current

widely used gzip utility, in that conforming decompressors

will be able to read data produced by the existing gzip

compressor.

The data format defined by this specification does not attempt to:

* Allow random Access to compressed data;

* Compress specialized data (e.g., raster graphics) as well

as the best currently available specialized algorithms.

A simple counting argument shows that no lossless compression

algorithm can compress every possible input data set. For the

format defined here, the worst case eXPansion is 5 bytes per 32K-

byte block, i.e., a size increase of 0.015% for large data sets.

English text usually compresses by a factor of 2.5 to 3;

executable files usually compress somewhat less; graphical data

such as raster images may compress much more.

1.2. Intended audience

This specification is intended for use by implementors of software

to compress data into "deflate" format and/or decompress data from

"deflate" format.

The text of the specification assumes a basic background in

programming at the level of bits and other primitive data

representations. Familiarity with the technique of Huffman coding

is helpful but not required.

1.3. Scope

The specification specifies a method for representing a sequence

of bytes as a (usually shorter) sequence of bits, and a method for

packing the latter bit sequence into bytes.

1.4. Compliance

Unless otherwise indicated below, a compliant decompressor must be

able to accept and decompress any data set that conforms to all

the specifications presented here; a compliant compressor must

produce data sets that conform to all the specifications presented

here.

1.5. Definitions of terms and conventions used

Byte: 8 bits stored or transmitted as a unit (same as an octet).

For this specification, a byte is exactly 8 bits, even on machines

which store a character on a number of bits different from eight.

See below, for the numbering of bits within a byte.

String: a sequence of arbitrary bytes.

1.6. Changes from previous versions

There have been no technical changes to the deflate format since

version 1.1 of this specification. In version 1.2, some

terminology was changed. Version 1.3 is a conversion of the

specification to RFCstyle.

2. Compressed representation overview

A compressed data set consists of a series of blocks, corresponding

to successive blocks of input data. The block sizes are arbitrary,

except that non-compressible blocks are limited to 65,535 bytes.

Each block is compressed using a combination of the LZ77 algorithm

and Huffman coding. The Huffman trees for each block are independent

of those for previous or subsequent blocks; the LZ77 algorithm may

use a reference to a duplicated string occurring in a previous block,

up to 32K input bytes before.

Each block consists of two parts: a pair of Huffman code trees that

describe the representation of the compressed data part, and a

compressed data part. (The Huffman trees themselves are compressed

using Huffman encoding.) The compressed data consists of a series of

elements of two types: literal bytes (of strings that have not been

detected as duplicated within the previous 32K input bytes), and

pointers to duplicated strings, where a pointer is represented as a

pair <length, backward distance>. The representation used in the

"deflate" format limits distances to 32K bytes and lengths to 258

bytes, but does not limit the size of a block, except for

uncompressible blocks, which are limited as noted above.

Each type of value (literals, distances, and lengths) in the

compressed data is represented using a Huffman code, using one code

tree for literals and lengths and a separate code tree for distances.

The code trees for each block appear in a compact form just before

the compressed data for that block.

3. Detailed specification

3.1. Overall conventions In the diagrams below, a box like this:

+---+

<-- the vertical bars might be missing

+---+

represents one byte; a box like this:

+==============+

represents a variable number of bytes.

Bytes stored within a computer do not have a "bit order", since

they are always treated as a unit. However, a byte considered as

an integer between 0 and 255 does have a most- and least-

significant bit, and since we write numbers with the most-

significant digit on the left, we also write bytes with the most-

significant bit on the left. In the diagrams below, we number the

bits of a byte so that bit 0 is the least-significant bit, i.e.,

the bits are numbered:

+--------+

76543210

+--------+

Within a computer, a number may occupy multiple bytes. All

multi-byte numbers in the format described here are stored with

the least-significant byte first (at the lower memory address).

For example, the decimal number 520 is stored as:

0 1

+--------+--------+

0000100000000010

+--------+--------+

^ ^

+ more significant byte = 2 x 256

+ less significant byte = 8

3.1.1. Packing into bytes

This document does not address the issue of the order in which

bits of a byte are transmitted on a bit-sequential medium,

since the final data format described here is byte- rather than

bit-oriented. However, we describe the compressed block format

in below, as a sequence of data elements of various bit

lengths, not a sequence of bytes. We must therefore specify

how to pack these data elements into bytes to form the final

compressed byte sequence:

* Data elements are packed into bytes in order of

increasing bit number within the byte, i.e., starting

with the least-significant bit of the byte.

* Data elements other than Huffman codes are packed

starting with the least-significant bit of the data

element.

* Huffman codes are packed starting with the most-

significant bit of the code.

In other Words, if one were to print out the compressed data as

a sequence of bytes, starting with the first byte at the

*right* margin and proceeding to the *left*, with the most-

significant bit of each byte on the left as usual, one would be

able to parse the result from right to left, with fixed-width

elements in the correct MSB-to-LSB order and Huffman codes in

bit-reversed order (i.e., with the first bit of the code in the

relative LSB position).

3.2. Compressed block format

3.2.1. Synopsis of prefix and Huffman coding

Prefix coding represents symbols from an a priori known

alphabet by bit sequences (codes), one code for each symbol, in

a manner such that different symbols may be represented by bit

sequences of different lengths, but a parser can always parse

an encoded string unambiguously symbol-by-symbol.

We define a prefix code in terms of a binary tree in which the

two edges descending from each non-leaf node are labeled 0 and

1 and in which the leaf nodes correspond one-for-one with (are

labeled with) the symbols of the alphabet; then the code for a

symbol is the sequence of 0's and 1's on the edges leading from

the root to the leaf labeled with that symbol. For example:

/\ Symbol Code

0 1 ------ ----

/ \ A 00

/\ B B 1

0 1 C 011

/ \ D 010

A / 0 1

/ D C

A parser can decode the next symbol from an encoded input

stream by walking down the tree from the root, at each step

choosing the edge corresponding to the next input bit.

Given an alphabet with known symbol frequencies, the Huffman

algorithm allows the construction of an optimal prefix code

(one which represents strings with those symbol frequencies

using the fewest bits of any possible prefix codes for that

alphabet). Such a code is called a Huffman code. (See

reference [1] in Chapter 5, references for additional

information on Huffman codes.)

Note that in the "deflate" format, the Huffman codes for the

various alphabets must not exceed certain maximum code lengths.

This constraint complicates the algorithm for computing code

lengths from symbol frequencies. Again, see Chapter 5,

references for details.

3.2.2. Use of Huffman coding in the "deflate" format

The Huffman codes used for each alphabet in the "deflate"

format have two additional rules:

* All codes of a given bit length have lexicographically

consecutive values, in the same order as the symbols

they represent;

* Shorter codes lexicographically precede longer codes.

We could recode the example above to follow this rule as

follows, assuming that the order of the alphabet is ABCD:

Symbol Code

------ ----

A 10

B 0

C 110

D 111

I.e., 0 precedes 10 which precedes 11x, and 110 and 111 are

lexicographically consecutive.

Given this rule, we can define the Huffman code for an alphabet

just by giving the bit lengths of the codes for each symbol of

the alphabet in order; this is sufficient to determine the

actual codes. In our example, the code is completely defined

by the sequence of bit lengths (2, 1, 3, 3). The following

algorithm generates the codes as integers, intended to be read

from most- to least-significant bit. The code lengths are

initially in tree[I].Len; the codes are produced in

tree[I].Code.

1) Count the number of codes for each code length. Let

bl_count[N] be the number of codes of length N, N >= 1.

2) Find the numerical value of the smallest code for each

code length:

code = 0;

bl_count[0] = 0;

for (bits = 1; bits <= MAX_BITS; bits++) {

code = (code + bl_count[bits-1]) << 1;

next_code[bits] = code;

}

3) Assign numerical values to all codes, using consecutive

values for all codes of the same length with the base

values determined at step 2. Codes that are never used

(which have a bit length of zero) must not be assigned a

value.

for (n = 0; n <= max_code; n++) {

len = tree[n].Len;

if (len != 0) {

tree[n].Code = next_code[len];

next_code[len]++;

}

Example:

Consider the alphabet ABCDEFGH, with bit lengths (3, 3, 3, 3,

3, 2, 4, 4). After step 1, we have:

N bl_count[N]

- -----------

2 1

3 5

4 2

Step 2 computes the following next_code values:

N next_code[N]

- ------------

1 0

2 0

3 2

4 14

Step 3 produces the following code values:

Symbol Length Code

------ ------ ----

A 3 010

B 3 011

C 3 100

D 3 101

E 3 110

F 2 00

G 4 1110

H 4 1111

3.2.3. Details of block format

Each block of compressed data begins with 3 header bits

containing the following data:

first bit BFINAL

next 2 bits BTYPE

Note that the header bits do not necessarily begin on a byte

boundary, since a block does not necessarily occupy an integral

number of bytes.

BFINAL is set if and only if this is the last block of the data

set.

BTYPE specifies how the data are compressed, as follows:

00 - no compression

01 - compressed with fixed Huffman codes

10 - compressed with dynamic Huffman codes

11 - reserved (error)

The only difference between the two compressed cases is how the

Huffman codes for the literal/length and distance alphabets are

defined.

In all cases, the decoding algorithm for the actual data is as

follows:

read block header from input stream.

if stored with no compression

skip any remaining bits in current partially

processed byte

read LEN and NLEN (see next section)

copy LEN bytes of data to output

otherwise

if compressed with dynamic Huffman codes

read representation of code trees (see

subsection below)

loop (until end of block code recognized)

decode literal/length value from input stream

if value < 256

copy value (literal byte) to output stream

otherwise

if value = end of block (256)

break from loop

otherwise (value = 257..285)

decode distance from input stream

move backwards distance bytes in the output

stream, and copy length bytes from this

position to the output stream.

end loop

while not last block

Note that a duplicated string reference may refer to a string

in a previous block; i.e., the backward distance may cross one

or more block boundaries. However a distance cannot refer past

the beginning of the output stream. (An application using a

preset dictionary might discard part of the output stream; a

distance can refer to that part of the output stream anyway)

Note also that the referenced string may overlap the current

position; for example, if the last 2 bytes decoded have values

X and Y, a string reference with <length = 5, distance = 2>

adds X,Y,X,Y,X to the output stream.

We now specify each compression method in turn.

3.2.4. Non-compressed blocks (BTYPE=00)

Any bits of input up to the next byte boundary are ignored.

The rest of the block consists of the following information:

0 1 2 3 4...

+---+---+---+---+================================+

LEN NLEN ... LEN bytes of literal data...

+---+---+---+---+================================+

LEN is the number of data bytes in the block. NLEN is the

one's complement of LEN.

3.2.5. Compressed blocks (length and distance codes)

As noted above, encoded data blocks in the "deflate" format

consist of sequences of symbols drawn from three conceptually

distinct alphabets: either literal bytes, from the alphabet of

byte values (0..255), or <length, backward distance> pairs,

where the length is drawn from (3..258) and the distance is

drawn from (1..32,768). In fact, the literal and length

alphabets are merged into a single alphabet (0..285), where

values 0..255 represent literal bytes, the value 256 indicates

end-of-block, and values 257..285 represent length codes

(possibly in conjunction with extra bits following the symbol

code) as follows:

Extra Extra Extra

Code Bits Length(s) Code Bits Lengths Code Bits Length(s)

---- ---- ------ ---- ---- ------- ---- ---- -------

257 0 3 267 1 15,16 277 4 67-82

258 0 4 268 1 17,18 278 4 83-98

259 0 5 269 2 19-22 279 4 99-114

260 0 6 270 2 23-26 280 4 115-130

261 0 7 271 2 27-30 281 5 131-162

262 0 8 272 2 31-34 282 5 163-194

263 0 9 273 3 35-42 283 5 195-226

264 0 10 274 3 43-50 284 5 227-257

265 1 11,12 275 3 51-58 285 0 258

266 1 13,14 276 3 59-66

The extra bits should be interpreted as a machine integer

stored with the most-significant bit first, e.g., bits 1110

represent the value 14.

Extra Extra Extra

Code Bits Dist Code Bits Dist Code Bits Distance

---- ---- ---- ---- ---- ------ ---- ---- --------

0 0 1 10 4 33-48 20 9 1025-1536

1 0 2 11 4 49-64 21 9 1537-2048

2 0 3 12 5 65-96 22 10 2049-3072

3 0 4 13 5 97-128 23 10 3073-4096

4 1 5,6 14 6 129-192 24 11 4097-6144

5 1 7,8 15 6 193-256 25 11 6145-8192

6 2 9-12 16 7 257-384 26 12 8193-12288

7 2 13-16 17 7 385-512 27 12 12289-16384

8 3 17-24 18 8 513-768 28 13 16385-24576

9 3 25-32 19 8 769-1024 29 13 24577-32768

3.2.6. Compression with fixed Huffman codes (BTYPE=01)

The Huffman codes for the two alphabets are fixed, and are not

represented explicitly in the data. The Huffman code lengths

for the literal/length alphabet are:

Lit Value Bits Codes

--------- ---- -----

0 - 143 8 00110000 through

10111111

144 - 255 9 110010000 through

111111111

256 - 279 7 0000000 through

0010111

280 - 287 8 11000000 through

11000111

The code lengths are sufficient to generate the actual codes,

as described above; we show the codes in the table for added

clarity. Literal/length values 286-287 will never actually

occur in the compressed data, but participate in the code

construction.

Distance codes 0-31 are represented by (fixed-length) 5-bit

codes, with possible additional bits as shown in the table

shown in Paragraph 3.2.5, above. Note that distance codes 30-

31 will never actually occur in the compressed data.

3.2.7. Compression with dynamic Huffman codes (BTYPE=10)

The Huffman codes for the two alphabets appear in the block

immediately after the header bits and before the actual

compressed data, first the literal/length code and then the

distance code. Each code is defined by a sequence of code

lengths, as discussed in Paragraph 3.2.2, above. For even

greater compactness, the code length sequences themselves are

compressed using a Huffman code. The alphabet for code lengths

is as follows:

0 - 15: Represent code lengths of 0 - 15

16: Copy the previous code length 3 - 6 times.

The next 2 bits indicate repeat length

(0 = 3, ... , 3 = 6)

Example: Codes 8, 16 (+2 bits 11),

16 (+2 bits 10) will expand to

12 code lengths of 8 (1 + 6 + 5)

17: Repeat a code length of 0 for 3 - 10 times.

(3 bits of length)

18: Repeat a code length of 0 for 11 - 138 times

(7 bits of length)

A code length of 0 indicates that the corresponding symbol in

the literal/length or distance alphabet will not occur in the

block, and should not participate in the Huffman code

construction algorithm given earlier. If only one distance

code is used, it is encoded using one bit, not zero bits; in

this case there is a single code length of one, with one unused

code. One distance code of zero bits means that there are no

distance codes used at all (the data is all literals).

We can now define the format of the block:

5 Bits: HLIT, # of Literal/Length codes - 257 (257 - 286)

5 Bits: HDIST, # of Distance codes - 1 (1 - 32)

4 Bits: HCLEN, # of Code Length codes - 4 (4 - 19)

(HCLEN + 4) x 3 bits: code lengths for the code length

alphabet given just above, in the order: 16, 17, 18,

0, 8, 7, 9, 6, 10, 5, 11, 4, 12, 3, 13, 2, 14, 1, 15

These code lengths are interpreted as 3-bit integers

(0-7); as above, a code length of 0 means the

corresponding symbol (literal/length or distance code

length) is not used.

HLIT + 257 code lengths for the literal/length alphabet,

encoded using the code length Huffman code

HDIST + 1 code lengths for the distance alphabet,

encoded using the code length Huffman code

The actual compressed data of the block,

encoded using the literal/length and distance Huffman

codes

The literal/length symbol 256 (end of data),

encoded using the literal/length Huffman code

The code length repeat codes can cross from HLIT + 257 to the

HDIST + 1 code lengths. In other words, all code lengths form

a single sequence of HLIT + HDIST + 258 values.

3.3. Compliance

A compressor may limit further the ranges of values specified in

the previous section and still be compliant; for example, it may

limit the range of backward pointers to some value smaller than

32K. Similarly, a compressor may limit the size of blocks so that

a compressible block fits in memory.

A compliant decompressor must accept the full range of possible

values defined in the previous section, and must accept blocks of

arbitrary size.

4. Compression algorithm details

While it is the intent of this document to define the "deflate"

compressed data format without reference to any particular

compression algorithm, the format is related to the compressed

formats produced by LZ77 (Lempel-Ziv 1977, see reference [2] below);

since many variations of LZ77 are patented, it is strongly

recommended that the implementor of a compressor follow the general

algorithm presented here, which is known not to be patented per se.

The material in this section is not part of the definition of the

specification per se, and a compressor need not follow it in order to

be compliant.

The compressor terminates a block when it determines that starting a

new block with fresh trees would be useful, or when the block size

fills up the compressor's block buffer.

The compressor uses a chained hash table to find duplicated strings,

using a hash function that operates on 3-byte sequences. At any

given point during compression, let XYZ be the next 3 input bytes to

be examined (not necessarily all different, of course). First, the

compressor examines the hash chain for XYZ. If the chain is empty,

the compressor simply writes out X as a literal byte and advances one

byte in the input. If the hash chain is not empty, indicating that

the sequence XYZ (or, if we are unlucky, some other 3 bytes with the

same hash function value) has occurred recently, the compressor

compares all strings on the XYZ hash chain with the actual input data

sequence starting at the current point, and selects the longest

match.

The compressor searches the hash chains starting with the most recent

strings, to favor small distances and thus take advantage of the

Huffman encoding. The hash chains are singly linked. There are no

deletions from the hash chains; the algorithm simply discards matches

that are too old. To avoid a worst-case situation, very long hash

chains are arbitrarily truncated at a certain length, determined by a

run-time parameter.

To improve overall compression, the compressor optionally defers the

selection of matches ("lazy matching"): after a match of length N has

been found, the compressor searches for a longer match starting at

the next input byte. If it finds a longer match, it truncates the

previous match to a length of one (thus producing a single literal

byte) and then emits the longer match. Otherwise, it emits the

original match, and, as described above, advances N bytes before

continuing.

Run-time parameters also control this "lazy match" procedure. If

compression ratio is most important, the compressor attempts a

complete second search regardless of the length of the first match.

In the normal case, if the current match is "long enough", the

compressor reduces the search for a longer match, thus speeding up

the process. If speed is most important, the compressor inserts new

strings in the hash table only when no match was found, or when the

match is not "too long". This degrades the compression ratio but

saves time since there are both fewer insertions and fewer searches.

5. References

[1] Huffman, D. A., "A Method for the Construction of Minimum

Redundancy Codes", Proceedings of the Institute of Radio

Engineers, September 1952, Volume 40, Number 9, pp. 1098-1101.

[2] Ziv J., Lempel A., "A Universal Algorithm for Sequential Data

Compression", IEEE Transactions on Information Theory, Vol. 23,

No. 3, pp. 337-343.

[3] Gailly, J.-L., and Adler, M., ZLIB documentation and sources,

available in ftp://ftp.uu.net/pub/archiving/zip/doc/

[4] Gailly, J.-L., and Adler, M., GZIP documentation and sources,

available as gzip-*.tar in ftp://prep.ai.mit.edu/pub/gnu/

[5] Schwartz, E. S., and Kallick, B. "Generating a canonical prefix

encoding." Comm. ACM, 7,3 (Mar. 1964), pp. 166-169.

[6] Hirschberg and Lelewer, "Efficient decoding of prefix codes,"

Comm. ACM, 33,4, April 1990, pp. 449-459.

6. Security Considerations

Any data compression method involves the reduction of redundancy in

the data. Consequently, any corruption of the data is likely to have

severe effects and be difficult to correct. Uncompressed text, on

the other hand, will probably still be readable despite the presence

of some corrupted bytes.

It is recommended that systems using this data format provide some

means of validating the integrity of the compressed data. See

reference [3], for example.

7. Source code

Source code for a C language implementation of a "deflate" compliant

compressor and decompressor is available within the zlib package at

ftp://ftp.uu.net/pub/archiving/zip/zlib/.

8. Acknowledgements

Trademarks cited in this document are the property of their

respective owners.

Phil Katz designed the deflate format. Jean-Loup Gailly and Mark

Adler wrote the related software described in this specification.

Glenn Randers-Pehrson converted this document to RFCand HTML format.

9. Author's Address

L. Peter Deutsch

Aladdin Enterprises

203 Santa Margarita Ave.

Menlo Park, CA 94025

Phone: (415) 322-0103 (AM only)

FAX: (415) 322-1734

EMail: <Ghost@aladdin.com>

Questions about the technical content of this specification can be

sent by email to:

Jean-Loup Gailly <gzip@prep.ai.mit.edu> and

Mark Adler <madler@alumni.caltech.edu>

Editorial comments on this specification can be sent by email to:

L. Peter Deutsch <ghost@aladdin.com> and

Glenn Randers-Pehrson <randeg@alumni.rpi.edu>