Function coverage ratio analysis method for logic test

Abstract

The invention relates to a function covering rate analyzing method of logic test, which comprises following steps: (a), inserting probe into the function branch of reference model; (b), when executing to the probe in the test process, using stat function to record the description information of probe into stat list; (c), when present mission is end, printing the record information of present function branch, to the log document; (d), when all tests are end, opening each log document of test, collecting all covering information of function branches, to generate tested function branch stat list; (e), scanning the reference model cost, to generate detecting point tree; (f), comparing said tested stat list and the detecting point tree, to obtain function covering rate information. And the inventive method has simple operation, reliable information and flexible operation on testing point.

Description

technical field [0001] The invention relates to a method for detecting whether the stimulus of a test case is sufficient, in particular to a method for analyzing the function coverage of a logic test. Background technique [0002] The functional requirements of logic can generally be translated into the form of "under XX incentives, the logic should respond to XX". In order to verify whether a certain functional requirement in the logic requirements specification is realized, it is necessary to apply various stimulus data to the logic (such as configuring registers, sending data packets to the logic, etc.), and then judging whether the response data of the logic is consistent with the requirements specification Consistent with the definition in . If the stimulus data applied to the logic is sufficient and the logic's response to the stimulus is correct, then the logic function is correctly implemented. The passing of the logic test needs to meet two conditions: the correct...

AI Technical Summary

Problems solved by technology

[0008] However, in this method, the tester defines the data set that the input data must cover according to the requirement specification. It is a human definition process, and it is also inevitable that there will be omissions.

On the other hand, due to the poor intuition of this kind of collection, the workload of the definition process is large and it is not easy to reuse, and it is also difficult to modify, so the actual effect is not ideal

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