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<HTML>
<HEAD>
<!-- This HTML file has been created by texi2html 1.51
from gperf.texi on 15 April 1998 -->
from gperf.texi on 20 August 2000 -->
<TITLE>User's Guide to gperf - 1 Introduction</TITLE>
<TITLE>Perfect Hash Function Generator - 2 Static search structures and GNU gperf</TITLE>
</HEAD>
<BODY>
Go to the <A HREF="gperf_1.html">first</A>, <A HREF="gperf_3.html">previous</A>, <A HREF="gperf_5.html">next</A>, <A HREF="gperf_11.html">last</A> section, <A HREF="gperf_toc.html">table of contents</A>.
<P><HR><P>
<H1><A NAME="SEC6" HREF="gperf_toc.html#TOC6">1 Introduction</A></H1>
<H1><A NAME="SEC6" HREF="gperf_toc.html#TOC6">2 Static search structures and GNU <CODE>gperf</CODE></A></H1>
<P>
<CODE>gperf</CODE> is a perfect hash function generator written in C++. It
transforms an <VAR>n</VAR> element user-specified keyword set <VAR>W</VAR> into
a perfect hash function <VAR>F</VAR>. <VAR>F</VAR> uniquely maps keywords in
<VAR>W</VAR> onto the range 0..<VAR>k</VAR>, where <VAR>k &#62;= n</VAR>. If
<VAR>k = n</VAR> then <VAR>F</VAR> is a <EM>minimal</EM> perfect hash function.
<CODE>gperf</CODE> generates a 0..<VAR>k</VAR> element static lookup table and a
pair of C functions. These functions determine whether a given
character string <VAR>s</VAR> occurs in <VAR>W</VAR>, using at most one probe
into the lookup table.
<A NAME="IDX2"></A>
</P>
<P>
<CODE>gperf</CODE> currently generates the reserved keyword recognizer for
lexical analyzers in several production and research compilers and
language processing tools, including GNU C, GNU C++, GNU Pascal, GNU
Modula 3, and GNU indent. Complete C++ source code for <CODE>gperf</CODE> is
available via anonymous ftp from <CODE>ics.uci.edu</CODE> and
<CODE>ftp.santafe.edu</CODE>. <CODE>gperf</CODE> was also distributed along with
the GNU libg++ library for several years. A highly portable,
functionally equivalent K&#38;R C version of <CODE>gperf</CODE> is archived in
comp.sources.unix, volume 20. Finally, a paper describing
<CODE>gperf</CODE>'s design and implementation in greater detail is available
in the Second USENIX C++ Conference proceedings.
A <STRONG>static search structure</STRONG> is an Abstract Data Type with certain
fundamental operations, e.g., <EM>initialize</EM>, <EM>insert</EM>,
and <EM>retrieve</EM>. Conceptually, all insertions occur before any
retrievals. In practice, <CODE>gperf</CODE> generates a <CODE>static</CODE> array
containing search set keywords and any associated attributes specified
by the user. Thus, there is essentially no execution-time cost for the
insertions. It is a useful data structure for representing <EM>static
search sets</EM>. Static search sets occur frequently in software system
applications. Typical static search sets include compiler reserved
words, assembler instruction opcodes, and built-in shell interpreter
commands. Search set members, called <STRONG>keywords</STRONG>, are inserted into
the structure only once, usually during program initialization, and are
not generally modified at run-time.
</P>
<P>
Numerous static search structure implementations exist, e.g.,
arrays, linked lists, binary search trees, digital search tries, and
hash tables. Different approaches offer trade-offs between space
utilization and search time efficiency. For example, an <VAR>n</VAR> element
sorted array is space efficient, though the average-case time
complexity for retrieval operations using binary search is
proportional to log <VAR>n</VAR>. Conversely, hash table implementations
often locate a table entry in constant time, but typically impose
additional memory overhead and exhibit poor worst case performance.
</P>
<P>
<A NAME="IDX3"></A>
<EM>Minimal perfect hash functions</EM> provide an optimal solution for a
particular class of static search sets. A minimal perfect hash
function is defined by two properties:
</P>
<UL>
<LI>
It allows keyword recognition in a static search set using at most
<EM>one</EM> probe into the hash table. This represents the "perfect"
property.
<LI>
The actual memory allocated to store the keywords is precisely large
enough for the keyword set, and <EM>no larger</EM>. This is the
"minimal" property.
</UL>
<P>
For most applications it is far easier to generate <EM>perfect</EM> hash
functions than <EM>minimal perfect</EM> hash functions. Moreover,
non-minimal perfect hash functions frequently execute faster than
minimal ones in practice. This phenomena occurs since searching a
sparse keyword table increases the probability of locating a "null"
entry, thereby reducing string comparisons. <CODE>gperf</CODE>'s default
behavior generates <EM>near-minimal</EM> perfect hash functions for
keyword sets. However, <CODE>gperf</CODE> provides many options that permit
user control over the degree of minimality and perfection.
</P>
<P>
Static search sets often exhibit relative stability over time. For
example, Ada's 63 reserved words have remained constant for nearly a
decade. It is therefore frequently worthwhile to expend concerted
effort building an optimal search structure <EM>once</EM>, if it
subsequently receives heavy use multiple times. <CODE>gperf</CODE> removes
the drudgery associated with constructing time- and space-efficient
search structures by hand. It has proven a useful and practical tool
for serious programming projects. Output from <CODE>gperf</CODE> is currently
used in several production and research compilers, including GNU C, GNU
C++, GNU Pascal, and GNU Modula 3. The latter two compilers are not yet
part of the official GNU distribution. Each compiler utilizes
<CODE>gperf</CODE> to automatically generate static search structures that
efficiently identify their respective reserved keywords.
</P>
<P><HR><P>