An evaluation method for execution time of function elements of network element management system

Abstract

The utility model discloses an evaluation method for function item execution time in a network element management system, used for increasing the testing efficiency of the network element management system, which mainly comprises, first, the direct proportional correlation factor and the inversely proportional inverse proportional correlation factor of the function item under test are ensured; second, a small data test is made for the function item under test, a test result of the execution time is obtained; third, according to the test result of the execution time, a processing efficiency constant of the network element management system is obtained; and finally, the execution time of the function item under test in the network element management system is obtained in the case of a large data size. The utility model has advantages that increasing testing efficiency.

Description

technical field [0001] The invention relates to the field of optical communication software, in particular to a method for evaluating the execution time of function items of a network element management system. Background technique [0002] The requirement of the modern network management system is to be able to support the management of mixed networking of multiple vendors and multiple types of equipment. With the increasing number of devices (a network element management system may need to manage hundreds or even thousands of devices) and the complexity of networking, higher requirements are placed on the management capabilities and performance of the network management. In order to meet the needs of operators and provide a network element management system with stable operation and excellent performance, in the research and development process of the network management system, especially in the product testing stage in order to obtain reliable information on network manag...

AI Technical Summary

Problems solved by technology

It takes a lot of time and energy to simply use manual testing methods to test the operating efficiency of a large amount of data, which has a serious impact on the testing of each stage of software development, and even delays the release time of the system. This is especially evident in iterative development. Iterative development requires the development of many versions in a short period of time. If all these versions are tested for operating efficiency, it will take a lot of time and energy

In addition, since the manual test obtains multiple sets of time-related values, it is difficult to analyze the operating efficiency of the system from these values, and it is difficult to analyze and summarize the data.

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