gperf is a "software-tool generating-tool" designed to automate the generation of perfect hash functions. This paper describes the features, algorithms, and object-oriented design and implementation strategies incorporated in gperf.Italso presents the results from an empirical comparison between gperf-generated recognizers and other popular techniques for reserved word lookup. gperf is distributed with the GNU libg++ library and is used to generate the keyword recognizers for the GNU C and GNU C++ compilers. 1 Introduction Perfect hash functions are a time and space efficient implementation of static search sets, which are ADTs with operations like initialize, insert,andretrieve. Static search sets are common in system software applications. Typical static search sets include compiler and interpreter reserved words, assembler instruction mnemonics, and shell interpreter builtin commands. Search set elements are called keywords.Key- words are inserted into the set once, usually at c...

Using a trace of address references, we compared the efficiency of several different hashing functions, such as cyclic redundancy checking (CRC) polynomials, Fletcher checksum, folding of address octets using the exclusive-or operation, and bit extraction from the address. Guidelines are provided for determining the size of hash mask required to achieve a specified level of performance. 1 INTRODUCTION The trend toward networks becoming larger and faster, addresses becoming larger, has impelled a need to explore alternatives for fast address recognition. This problem is actually a special case of the general problem of searching through a large data base and finding the information associated with a given key. For example, Datalink adapters on local area networks (LAN) need to recognize the multicast destination addresses of frames on the LAN. Bridges, used to interconnect two or more LANs, have to recognize the destination addresses of every frame and decide quickly whether to receive...

String hashing is a fundamental operation, used in countless applications where fast access to distinct strings is required. In this paper we describe a class of string hashing functions and explore its performance. In particular, using experiments with both small sets of keys and a large key set from a text database, we show that it is possible to achieve performance close to that theoretically predicted for hashing functions. We also consider criteria for choosing a hashing function and use them to compare our class of functions to other methods for string hashing. These results show that our class of hashing functions is reliable and efficient, and is therefore an appropriate choice for general-purpose hashing.

There are several advantages to be gained by storing the lexicon of a full text database in main memory. In this paper we describe how to use a compressed inverted file index to search such a lexicon for entries that match a pattern or partially specified term. Our experiments show that this method provides an effective compromise between speed and space, running orders of magnitude faster than brute force search, but requiring less memory than other pattern-matching data structures; indeed, in some cases requiring less memory than would be consumed by a single pointer to each string. The pattern search method is based on text indexing techniques and is a successful adaptation of inverted files to main memory databases.

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