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Automatic test method based on machine learning and terminal

A technology of automated testing and machine learning, applied in software testing/debugging, instrumentation, error detection/correction, etc., can solve problems such as time-consuming, cumbersome operation, and low testing efficiency, and achieve the effect of saving time and improving testing efficiency

Active Publication Date: 2018-11-06
FUJIAN TIANQUAN EDUCATION TECH LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] However, the existing automated interface testing method using image matching technology has the following disadvantages: it is necessary to write corresponding test codes for the operable controls of the screenshots, and when the product development iterations are frequent and the interface changes greatly, the test engineer needs to re-modify the test Use cases, and re-screenshots of the operable controls in the changing part of the product interface, modify the test code, the operation is cumbersome, time-consuming, and the test efficiency is not high

Method used

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  • Automatic test method based on machine learning and terminal
  • Automatic test method based on machine learning and terminal
  • Automatic test method based on machine learning and terminal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0062] Please refer to figure 1 , an automated testing method based on machine learning, including steps:

[0063] S01. Classify the interactive controls of all interfaces of the product to be tested, and write operation codes corresponding to the classified interactive controls respectively;

[0064] S02. According to the classification, take screenshots of the interactive controls in all the interfaces of the product to be tested, respectively generate screenshots corresponding to each category, and use the machine learning framework to perform model training on the screenshots corresponding to each category until it is trained The detection accuracy of the model is greater than a preset value;

[0065] S1. Use the model trained by the machine learning framework to detect the current interface of the product to be tested, determine all the interactive controls on the current interface, and circle all the interactive controls on the current interface;

[0066] Wherein, the ...

Embodiment 2

[0072] The difference between this embodiment and Embodiment 1 is that in the step S3, the interactive control is tested while recording it, and after the test is completed, a recording file corresponding to the test case is generated, and the recording file is recorded. to store;

[0073] After the step S3, also include steps:

[0074] S4. Receive the selected recorded test case, and test the interactive control corresponding to the data record in the current interface of the product to be tested in real time according to the data record of the selected recorded test case;

[0075] The data records saved during the testing process can not only be applied to software testing, but also in subsequent software applications, if common repetitive operations need to be performed, they can be saved as common operation records and played back when needed.

Embodiment 3

[0077] Please refer to figure 2 , an automated testing terminal 1 based on machine learning, comprising a memory 2, a processor 3, and a computer program stored on the memory 2 and operable on the processor 3, and the processor 3 executes the computer program The program realizes each step in the first embodiment.

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Abstract

The invention provides an automatic test method based on machine learning and terminal. The method comprises the steps of detecting a current interface of a to-be-tested product through utilization ofa model trained by a machine learning frame, determining all interactable controls of the current interface, and circling all interactable controls of the current interface; receiving a test case forone interactable control, wherein the test case is described through voices, converting the voices into texts, and converting the texts into data records according to a preset format; and calling operation codes corresponding to the interactable control in real time according to the data records, and testing the interactable control. Test codes do not need to be written, an operation process canbe described through the voices, the corresponding data records are generated, the interactable control is tested in real time, the time of writing interface test automatic scripts is greatly reduced,and the test efficiency is improved.

Description

technical field [0001] The invention relates to the field of software testing, in particular to a machine learning-based automatic testing method and a terminal. Background technique [0002] Automated testing technology has been widely used in software development, which can greatly improve the efficiency of testing, reduce the influence of human factors, and shorten the software development cycle. Among them, the interface automation testing technology using image matching technology is getting more and more attention. Its testing process is as follows: test engineers write automated test cases, then take screenshots of the operable controls on the product interface, then write corresponding test codes, and start. [0003] However, the existing automated interface testing method using image matching technology has the following disadvantages: it is necessary to write corresponding test codes for the operable controls of the screenshots, and when the product development it...

Claims

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Application Information

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IPC IPC(8): G06F11/36G06N99/00
CPCG06F11/3684G06F11/3692
Inventor 刘德建李思林琛
Owner FUJIAN TIANQUAN EDUCATION TECH LTD
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