How do I debug UIAutomator scripts with Eclipse

本文详细介绍了如何在Eclipse中设置DDMS视角进行UIAutomator脚本的远程调试。包括配置远程调试环境、启动UIAutomator脚本以及设置断点等步骤。

http://stackoverflow.com/questions/21978292/how-do-i-debug-uiautomator-scripts-with-eclipse.

以下内容是转载,如果侵犯您的权利,请通知我删除。


  1. Set up a DDMS perspective in Eclipse by clicking Window > Open Perspective > Other... > DDMS. You should see your device listed in the Devices tab, assuming you have an emulator/device running.
  2. Set up a remote debugging configuration. To do this go to Run > Debug Configurations...
  3. Right click on Remote Java Application from the left hand panel and click 'New' to create a new configuration.
  4. In the connection properties use localhost and port 8700. In my case I am using an emulator that is running on my local development machine. The default port for DDMS is 8700. If this is not the case for your setup you can check what port needs to be from the DDMS perspective after the UI Automator script is run in debug mode. (See steps 7-9 below) 
  5. Ensure that the project you've selected is the UI Automation project that you will be running. In the "Source" tab you may also add the UI Automation project there also. (Not sure if this is mandatory or not)
  6. Click "Apply" and then close.
  7. Now we will start running the UI Automator script with the debug option using the command line. For my example the command is (all on one line):adb shell uiautomator runtest AndroidUIAutomation.jar -c com.example.uiautomation.TestUiAutomation -e debug true
  8. It will then say:Sending WAIT chunk
  9. In Eclipse go into the DDMS perspective. Under the Devices tab you should see a process with a little red bug symbol. Next to it will be a question mark. In the last column in the table there will be two port numbers such as 8602/8700. The port 8700 is the one you will connect your remote debugging session to. This is what should be configured in step 4 above.
  10. Now you are ready to start remote debugging. Set a breakpoint somewhere in the UI Automator script. Then debug by going to Run > Debug Configurations... and then select the Remote Java Application configuration that you created earlier and then click on "Debug".


根据原作 https://pan.quark.cn/s/459657bcfd45 的源码改编 Classic-ML-Methods-Algo 引言 建立这个项目,是为了梳理和总结传统机器学习(Machine Learning)方法(methods)或者算法(algo),和各位同仁相互学习交流. 现在的深度学习本质上来自于传统的神经网络模型,很大程度上是传统机器学习的延续,同时也在不少时候需要结合传统方法来实现. 任何机器学习方法基本的流程结构都是通用的;使用的评价方法也基本通用;使用的一些数学知识也是通用的. 本文在梳理传统机器学习方法算法的同时也会顺便补充这些流程,数学上的知识以供参考. 机器学习 机器学习是人工智能(Artificial Intelligence)的一个分支,也是实现人工智能最重要的手段.区别于传统的基于规则(rule-based)的算法,机器学习可以从数据中获取知识,从而实现规定的任务[Ian Goodfellow and Yoshua Bengio and Aaron Courville的Deep Learning].这些知识可以分为四种: 总结(summarization) 预测(prediction) 估计(estimation) 假想验证(hypothesis testing) 机器学习主要关心的是预测[Varian在Big Data : New Tricks for Econometrics],预测的可以是连续性的输出变量,分类,聚类或者物品之间的有趣关联. 机器学习分类 根据数据配置(setting,是否有标签,可以是连续的也可以是离散的)和任务目标,我们可以将机器学习方法分为四种: 无监督(unsupervised) 训练数据没有给定...
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值