Abstract: The aim of software maintenance is to maintain
the software system in accordance with advancement in software
and hardware technology. One of the early works on software
maintenance is to extract information at higher level of abstraction. In
this paper, we present the process of how to design an information
extraction tool for software maintenance. The tool can extract the
basic information from old programs such as about variables, based
classes, derived classes, objects of classes, and functions. The tool
have two main parts; the lexical analyzer module that can read the
input file character by character, and the searching module which
users can get the basic information from the existing programs. We
implemented this tool for a patterned sub-C++ language as an input
file.
Abstract: We report in this paper the model adopted by our
system of continuous speech recognition in Arab language SySRA
and the results obtained until now. This system uses the database
Arabdic-10 which is a corpus of word for the Arab language and
which was manually segmented. Phonetic decoding is represented
by an expert system where the knowledge base is translated in the
form of production rules. This expert system transforms a vocal
signal into a phonetic lattice. The higher level of the system takes
care of the recognition of the lattice thus obtained by deferring it in
the form of written sentences (orthographical Form). This level
contains initially the lexical analyzer which is not other than the
module of recognition. We subjected this analyzer to a set of
spectrograms obtained by dictating a score of sentences in Arab
language. The rate of recognition of these sentences is about 70%
which is, to our knowledge, the best result for the recognition of the
Arab language. The test set consists of twenty sentences from four
speakers not having taken part in the training.