物件導向軟體之架構(Object-Oriented Software Construction)探討

The state of the art in data compression is arithmetic coding, not the better-known Huffman method. Arithmetic coding gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.

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Arithmetic coding for data compression

We survey the current techniques to cope with the problem of string matching that allows errors. This is becoming a more and more relevant issue for many fast growing areas such as information retrieval and computational biology. We focus on online searching and mostly on edit distance, explaining the problem and its relevance, its statistical behavior, its history and current developments, and the central ideas of the algorithms and their complexities. We present a number of experiments to compare the performance of the different algorithms and show which are the best choices. We conclude with some directions for future work and open problems.

/pdf/a-guided-tour-to-approximate-string-matching-22fowlmq5b.pdf

A guided tour to approximate string matching

An edited volume containing data structures and algorithms for information retrieved including a disk with examples written in C. For programmers and students interested in parsing text, automated indexing, its the first collection in book form of the basic data structures and algorithms that are critical to the storage and retrieval of documents.

https://hornad.fei.tuke.sk/~genci/Vyucba/OOBDS/Archiv/Podklady/TExtoveIS&IR/Information%20Retrieval%20Data%20Structures%20&%20Algorithms.PDF

Information Retrieval: Data Structures and Algorithms

Program analysis utilizes static techniques for computing reliable information about the dynamic behavior of programs. Applications include compilers (for code improvement), software validation (for detecting errors) and transformations between data representation (for solving problems such as Y2K). This book is unique in providing an overview of the four major approaches to program analysis: data flow analysis, constraint-based analysis, abstract interpretation, and type and effect systems. The presentation illustrates the extensive similarities between the approaches, helping readers to choose the best one to utilize.

Principles of program analysis

K2 is a new approach to solving two of the most difficult problems in the area of programming-in-the-large — mastery of the structural complexity of large software systems and effective presentation of the information accumulated during the development concerned with the specification, design, integration, and maintenance of software systems at a higher level than that of a single module. The major objective of K2 is to effectively represent and manipulate the building blocks of a software system and their myriad dependencies, thereby aiding the development phases of the project.The K2 environment is an integrated collection of tools that allows the members of a complex software project to organize development information by manipulating system description documents of various types and by establishing links between those documents. System description documents support the project from the early specification and design phases through the long-term maintenance phases. The K2 system will improve th...

Presentation Of Software Development Information In K2

An incremental parser generator would be a desirable tool for use in compiler implementation projects or for experimental use in designing new languages. It would allow the tool user to incrementally add or remove production rules from a grammar while maintaining correct parse tables, and would report grammatical problems to the user at the earliest possible moment. ILALR is such an incremental parser generator for the LALR(1) class of grammars. It uses incremental algorithms for computing the LALR(1) parser tables.

/pdf/ilalr-an-incremental-generator-of-lalr-1-parsers-kttr2i0cku.pdf

ILALR: An Incremental Generator of LALR(1) Parsers

Non-backtracking recursive descent parsers are easy to create but suffer from the disadvantage that they are limited to the relatively small LL(κ) class of grammars. Recursive ascent parsers can be built for the much larger LR(κ) class of grammars, but they are likely be too large to be useful and manual insertion of semantic action code into the parsers would require considerable skill. A composite approach, dubbed ‘recursive ascent-descent parsing’ or XLC(1) parsing, and which is related to left-corner parsing, solves all the problems. The parser has two parts — a top-down part and a bottom-up part. Either or both parts may be implemented as a collection of recursive functions or by a table-driven parsing algorithm. When a table-driven implementation of the bottom-up part is used, any syntax error recovery scheme applicable to LR parsers can be employed. Small, fast, implementations of the parsers are possible.

Recursive ascent-descent parsers

We present a representation for XML documents, derived from Warren's representation of Prolog terms in the Warren Abstract Machine (WAM)*, which permits very efficient access and update operations. Our scheme is implemented in CXMLParser, a non-validating XML processor. We present the results of a performance comparison with two other XML processors, which show that CXMLParser is faster by a factor of 2.2 to 4.3 than its nearest competitor.

R. Nigel Horspool

Papers

Presentation Of Software Development Information In K2

ILALR: An Incremental Generator of LALR(1) Parsers

Recursive ascent-descent parsers

Expeditious XML Processing