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Test case selection method and device applied to distributed storage system and medium

A distributed storage and test case technology, applied in software testing/debugging, version control, software maintenance/management, etc., can solve the problems of large subjective factors in test regression range, reduced test efficiency, and time-consuming, etc., to reduce Dependence on human experience, improving test reliability, and reducing workload

Pending Publication Date: 2022-04-12
SHANGHAI DRAGONNET TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] 1. The range of test regression has a lot of subjective factors. If the range estimate is too small, there may be test omissions and software quality problems. If the range estimate is too large, it will consume time and reduce test efficiency.

Method used

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  • Test case selection method and device applied to distributed storage system and medium
  • Test case selection method and device applied to distributed storage system and medium
  • Test case selection method and device applied to distributed storage system and medium

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0037] Such as figure 1 As shown, the present embodiment provides a method for selecting test cases applied to a distributed storage system, comprising the following steps: obtaining a code change function list of the software code of the version to be tested relative to the software code of the reference version; based on the code change function list And software information generates version change information, and software information includes file ID, module ID, CPU type, network type and author etc.; With described version change information as the input of a trained test case scoring model, obtain preset test case concentration The confidence level of each test case is to calculate the probability that each function that undergoes code changes will affect the results of the preset test cases. Specifically, the test case scoring model obtains software change characteristics based on the version change information, And obtain the use case characteristics of each test in t...

test Embodiment ID

[0048] Historical defect data has fields such as test case ID, software historical version, and defect level.

[0049] Format in data: FunctionID::CaseID::Rating

[0050] In this embodiment, Rating is the target to be learned by the test case scoring model.

[0051] 2. Data preprocessing

[0052] In this embodiment, different data preprocessing is performed on data in different fields:

[0053] FunctionID, FileID, ModuleID and AuthorID do not change.

[0054] Gender field: Need to convert 'F' and 'M' into 0 and 1.

[0055] CPU field: According to the actual situation of the system, it supports three types of CPUs: Intel, AMD, and ARM, and convert them into three consecutive numbers 0~2.

[0056] Network field: According to the actual situation of the system, it supports three types of networks: Ethernet, RDMA, and RoCE, and converts them into three consecutive numbers 0-2.

[0057] Genres field: It is a categorical field, which needs to be converted into a number. In the...

Embodiment 2

[0071] This embodiment provides a test case selection device applied to a distributed storage system, including one or more processors, memory and one or more programs stored in the memory, the one or more programs include Execute the instructions of the test case selection method applied to the distributed storage system as described in Embodiment 1.

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Abstract

The invention relates to a test case selection method and device applied to a distributed storage system and a medium. The method comprises the following steps: acquiring a code change function list of a to-be-tested version software code relative to a reference version software code; generating version change information based on the code change function list and software information; the version change information serves as input of a trained test case scoring model, and the confidence coefficient of each test case in a preset test case set is obtained; taking the test case with the confidence greater than a confidence threshold as a recommended case; the test case scoring model is constructed based on a convolutional neural network, and training samples adopted during training comprise historical code change information, feature information of test cases and historical defect information corresponding to the test cases. Compared with the prior art, the method has the advantages that the test case selection efficiency can be effectively improved, and the like.

Description

technical field [0001] The invention relates to the technical field of software testing, in particular to a test case selection method, device and medium applied to a distributed storage system. Background technique [0002] Software testing is a key factor in software development. In order to ensure a comprehensive and complete test of the system to be tested, the test types can usually be divided into: functional test, reliability test, performance test, security test and other types. For distributed storage systems, due to the high complexity of the systems involved, there are extremely high requirements for data consistency and high availability of the system. Therefore, each version iteration needs to introduce regressions to existing functions. [0003] So how to reasonably confirm the scope of regression testing and how to improve the efficiency of testing while ensuring quality has become a pain point and difficulty for testers. For now, the selection of test case...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F8/71G06F11/36
Inventor 陈轩
Owner SHANGHAI DRAGONNET TECH
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