A Hybrid Parallel Execution Model for Logic Based Requirement Specifications (Invited Paper)
Author(s) -
Jeffrey J. P. Tsai,
Bing Li
Publication year - 1999
Publication title -
ajis. australasian journal of information systems/ajis. australian journal of information systems/australian journal of information systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.351
H-Index - 18
eISSN - 1326-2238
pISSN - 1039-7841
DOI - 10.3127/ajis.v6i2.291
Subject(s) - computer science , logic model , programming language , computer architecture , software engineering , sociology , social science
It is well known that undiscovered errors in a requirements specification is extremely expensive to be fixed when discovered in the software maintenance phase. Errors in the requirement phase can be reduced through the validation and verification of the requirements specification. Many logic-based requirements specification languages have been developed to achieve these goals. However, the execution and reasoning of a logic-based requirements specification can be very slow. An effective way to improve their performance is to execute and reason the logic-based requirements specification in parallel. In this paper, we present a hybrid model to facilitate the parallel execution of a logic-based requirements specification language. A logic-based specification is first applied by a data dependency analysis technique which can find all the mode combinations that exist within a specification clause. This mode information is used to support a novel hybrid parallel execution model, which combines both top-down and bottom-up evaluation strategies. This new execution model can find the failure in the deepest node of the search tree at the early stage of the evaluation, thus this new execution model can reduce the total number of nodes searched in the tree, the total processes needed to be generated, and the total communication channels needed in the search process. A simulator has been implemented to analyze the execution behavior of the new model. Experiments show significant improvement based on several criteria
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