DocumentCode :
306468
Title :
An automatic software generation approach for easier distributed programming
Author :
Wong, Allan K Y ; Yeung, Daniel S.
Author_Institution :
Dept. of Comput., Hong Kong Polytech. Univ., Hung Hom, Hong Kong
Volume :
2
fYear :
1996
fDate :
14-17 Oct 1996
Firstpage :
1553
Abstract :
The proposed automatic software generation approach makes distributed programming easier by minimizing the steps leading to a programming solution. The user needs to provide only a high level asynchronous parallel programming language (APPL) program which is, in effect, a pseudocode specification. With this the precompiler can automatically instantiate the necessary program objects by the object-oriented approach. For every APPL program, the precompiler also produces a program objects dictionary consisting of descriptors. Each descriptor represents a program object in the APPL program. During execution a program objects dictionary becomes an entry in the local system distributed objects dictionary which is maintained by the kernel. Kernels continually exchange the current values of the attributes in the descriptors. By sampling and organizing the values of the descriptors, program visualization and reverse software engineering can be achieved
Keywords :
automatic programming; formal specification; object-oriented programming; parallel programming; reverse engineering; software engineering; software libraries; visual programming; asynchronous parallel programming language; automatic software generation; descriptors; distributed programming; object class library; object-oriented method; objects dictionary; precompiler; program visualization; pseudocode specification; reverse software engineering; Automatic programming; Dictionaries; Distributed computing; Kernel; Load management; Organizing; Parallel programming; Relays; Sampling methods; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1996., IEEE International Conference on
Conference_Location :
Beijing
ISSN :
1062-922X
Print_ISBN :
0-7803-3280-6
Type :
conf
DOI :
10.1109/ICSMC.1996.571379
Filename :
571379
Link To Document :
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