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# software_testing_server
基于机器学习分类算法的软件缺陷分析与预测系统,使用了Vue、Springboot以及MySQL开发,此处只有后端
项目来自北京交通大学大三上半学期机器学习团队项目
本人在其中主要负责服务器搭建以及后端的开发以及后续项目测试
开发时主要使用GitLab进行协作开发
项目功能:账户及用户信息管理功能、各算法训练、各算法预测(logistic、decision tree、kmeans、感知机、朴素贝叶斯)
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# 实训后端
## Getting started
To make it easy for you to get started with GitLab, here's a list of recommended next steps.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)!
## Add your files
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
```
cd existing_repo
git remote add origin http://nas.noneid.life/STMLEXP/server.git
git branch -M main
git push -uf origin main
```
## Integrate with your tools
- [ ] [Set up project integrations](http://nas.noneid.life/STMLEXP/server/-/settings/integrations)
## Collaborate with your team
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/)
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Automatically merge when pipeline succeeds](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Test and Deploy
Use the built-in continuous integration in GitLab.
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html)
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing(SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
***
# Editing this README
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thank you to [makeareadme.com](https://www.makeareadme.com/) for this template.
## Suggestions for a good README
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information.
## Name
Choose a self-explaining name for your project.
## Description
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors.
## Badges
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
## Visuals
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method.
## Installation
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
## Usage
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
## Support
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## Contributing
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You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
## Authors and acknowledgment
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>>>>>>> c33bc00 (Initial commit)
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基于机器学习分类算法的软件缺陷分析与预测系统后端完整源码+说明(使用Vue+Springboot+MySQL开发).zip (418个子文件)
TrainHistoryServiceImpl.class 14KB
DecisionTree.class 10KB
ControllerDecisionTree.class 8KB
FileController.class 7KB
AccountServiceImpl.class 7KB
LogisticR.class 7KB
PredictHistoryServiceImpl.class 7KB
Perpcetron.class 6KB
CsvReader.class 5KB
Files.class 5KB
UserInfo.class 5KB
TrainHistoryController.class 5KB
CsvReader.class 5KB
KNN.class 5KB
Model.class 5KB
CodeGenerator.class 5KB
Result.class 4KB
Dataset.class 4KB
Kmeans.class 4KB
TrainHistory.class 4KB
JwtInterceptor.class 4KB
AccountController.class 3KB
TokenUtils.class 3KB
ControllerPerpcetron.class 3KB
ControllerLogisticR.class 3KB
UserInfoServiceImpl.class 3KB
PredictHistory.class 3KB
PredictHistoryController.class 3KB
InterceptorConfig.class 3KB
Account.class 3KB
ControllerKmeans.class 2KB
SwaggerConfig.class 2KB
CsvReader.class 2KB
Node.class 2KB
ControllerKNN.class 2KB
ModelServiceImpl.class 2KB
OutputPredict.class 2KB
DatasetServiceImpl.class 2KB
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MybatisPlusConfig.class 1KB
IPredictHistoryService.class 1KB
IAccountService.class 1KB
EDistance.class 1024B
MDistance.class 984B
SoftwareTestingServerApplication.class 883B
IUserInfoService.class 765B
TestSet.class 533B
IDatasetService.class 518B
TrainSet.class 516B
Point.class 514B
Set.class 508B
IModelService.class 508B
LoginToken.class 490B
PassToken.class 488B
PredictHistoryMapper.class 461B
TrainHistoryMapper.class 455B
DatasetMapper.class 440B
ModelMapper.class 434B
UserInfoMapper.class 431B
AccountMapper.class 428B
FileMapper.class 420B
Dis.class 302B
Constants.class 286B
mvnw.cmd 7KB
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JDT.csv 233KB
.gitignore 233B
software_testing_server.iml 28KB
server.iml 336B
software_testing_server-0.0.1-SNAPSHOT.jar 60.82MB
inputFiles.lst 7KB
createdFiles.lst 4KB
inputFiles.lst 0B
createdFiles.lst 0B
README.md 7KB
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mvnw 10KB
software_testing_server-0.0.1-SNAPSHOT.jar.original 528KB
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pom.properties 77B
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