Discovery method for MOF memory pool conflict operation based on constraint deduction

Abstract

The invention relates to a discovery method for MOF memory pool conflict operation based on constraint deduction. The method is technically characterized by comprising the steps that internal activities influencing good format constraint are defined, and a corresponding relation between the internal activities and MOF construction activities is established; the good format constraint is simplified; a discovery map is established; the discovery map is marked; the internal activities are acquired; and potential operation violating the constraint is determined. According to the method, the internal activities possibly violating constraint conditions are deduced, then the potential operation violating the constraint conditions is deduced, and finally constraint conditions irrelevant to given operation can be deduced. The constraint conditions irrelevant to the given operation are removed from a constraint detection process after execution of the operation, and therefore the efficiency of the process can be remarkably improved. The method can be widely applied to the constraint detection field.

Description

technical field [0001] The invention belongs to the technical field of repository systems, in particular to a method for discovering conflicting operations of MOF repository based on constraint deduction. Background technique [0002] Today, the Meta Object Facility (MOF) has become the internationally accepted and adopted metadata repository system standard. As an important part of the MOF repository system, the well-formed constraints defined based on the Object Constraint Language OCL stipulate the conditions that all states of the system must comply with. The content of the repository system will be changed due to the execution of the operation, so it must be ensured that the state of the repository system after the execution of the operation does not violate the well-formed constraints in the meta-level. [0003] However, this task becomes quite difficult due to the following two reasons: On the one hand, the organization of metadata in the repository system presents a...

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Problems solved by technology

Similar research exists in the field of deductive database and relational database. The solution adopted is mainly to convert OCL constraints into logical expressions or SQL expressions, and then design algorithms on this basis to infer the exact PEA set of given constraints. For example, Duboisset et al. (Duboisset M, etal. Integrating the calculus-based method into OCL: Study of expressiveness and code generation, Proc of the 18th Int Workshop on Database and Expert Systems Applications. Piscataway, NJ: IEEE, 2007: 502-506), Pinet et al. (Pinet F, Duboisset M, Demuth B, et al. Constraints modeling in agricultural databases, Advances in Modeling Agricultural Systems. Berlin: Springer, 2009: 1-11), Donald C, Narayanaswamy K. Using first -order logic to query heterogeneous internet datasources, Proc of the 2015Int Conf on Soft Computing and Software Engineering. Holand: Academic Press, Elsevier, 2015:1-8), Demuth et al. (Demuth B, Hussmann H, Loecher S. OCL as a specification language for business rules indatabase applications, LNCS 2185: Proc of the 4th Conf on UML. Berlin: Springer, 2006: 104-117), Chen et al. (Chen Lianggang et al. Interval Constrained Database Query Language: ISQL. Computer Research and Development, 2000,37(6): 677-683), however, since OCL constraints include many complex structures such as negation, recursion, packet semantics, aggregation operations, etc., the processing ability of the proposed algorithm is difficult to cover all OCL constraints mechanism

Although some algorithms have improved this to support all mechanisms of OCL constraints, the high complexity of the processing logic has led to low efficiency of the algorithm (for their limitations, please refer to the discussion of Siva et al. (Siva S, et al. al. Constraint processing in relational database systems: From theory to implementation, Procof the 25th ACM Symp on Applied Computing. New York: ACM, 2010: 2066-2070))

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