Open source code detection method and device, and computer readable storage medium

Abstract

The embodiment of the invention relates to the technical field of open source code detection, and discloses an open source code detection method, which comprises the following steps of: receiving an open source code entity, and establishing a neural network model of the open source code entity; training the neural network model; after the training of the neural network model is completed, receiving a to-be-detected mixed source code entity; performing preset processing on the mixed source code entity, and inputting the processed data into a trained neural network model for retrieval; and judging whether the mixed source code entity is matched with the open source code entity according to a retrieval result. According to the method, the open source code detection technology combining the static characteristics and the neural network is utilized, the false alarm rate is reduced by utilizing the artificial intelligence technology, and the detection cost is reduced along with gradual maturity of the trained model by training the neural model.

Description

technical field [0001] The embodiments of the present invention relate to the technical field of open source code detection, and in particular to an open source code detection method, device, and computer-readable storage medium. Background technique [0002] Open source code refers to publicly available computer source code that is freely accessible and usable by the programmers who developed the code. Open source code can be used in a variety of scenarios, such as: saving time and effort in programming and debugging by obtaining open source unit test code; porting open source code to scenarios where users do not have sufficient experience or knowledge; adding common options such as graphics support , print, etc. [0003] Despite the many benefits of open source code, open source code can also pose risks. Using open source code involves licensing issues. Each of these licenses may impose specific restrictions or requirements on users or user projects developed using open...

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Problems solved by technology

[0007] However, the inventors found that there are at least the following problems in the prior art: (1) the problem of high false alarm rate cannot be solved; token calculation, especially the problem of high CPU consumption and crash caused by concurrent computing scenarios, cannot really improve detection efficiency

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