Memory prediction method and device suitable for dependency analysis tool

Abstract

The invention discloses a memory prediction method and device suitable for a dependency analysis tool, and the method specifically comprises the steps of extracting a source code file from a Java program package file; analyzing the extracted source code file, generating an abstract syntax tree, and obtaining the number of the instance objects of each type of node class in the abstract syntax treegenerated by each source code file; calculating the size of a memory occupied by each type of node type instance objects; calculating the memory occupied by the abstract syntax tree generated by eachsource code file; and calculating the memory size required by the whole Java program package. According to the method, the memory is predicted when the dependency analysis tool runs, so that the dependency analysis tool container can be allocated to the container running nodes with enough memory resources through the predicted memory every time, and the running stability of the dependency analysistool and the running stability of a distributed code detection system are ensured.

Description

technical field [0001] The invention relates to a memory prediction method and device suitable for dependency analysis tools, belonging to the technical field of computer memory management. Background technique [0002] With the maturity of container technology and the continuous improvement of container orchestration tools, deploying and developing systems in the cloud has become the choice of more and more enterprises. The container cloud mainly uses the container orchestration tool to provide users with an automatic deployment method for automatically deploying containers to nodes. However, if the user does not specify the required CPU and memory resources for the container, the container can get at most the resources on the node where the container is located. Remaining memory and CPU resources. [0003] At this stage, the subject's source file dependency analysis tool needs to be deployed and run in the container cloud environment. The dependency analysis tool analyze...

AI Technical Summary

Problems solved by technology

During the analysis process, these syntax tree structures are stored in memory. If you do not set enough memory resources for the dependency analysis tool container, there may be insufficient memory resources required by the dependency analysis tool during the analysis process. Will lead to a sharp decline in tool performance or even cause analysis failure

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