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Graphic interface automated test method

A technology of automated testing and graphical interface, applied in the application of image technology in automated software testing, the field of machine learning, can solve problems such as fatigue and dullness, and achieve the effect of improving efficiency, improving accuracy, and realizing automation

Active Publication Date: 2016-09-21
NANJING UNIV
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AI Technical Summary

Problems solved by technology

When performing functional tests manually, relying on human eyes to observe interface recognition errors is easy to make people tired and very boring

Method used

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Examples

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Embodiment Construction

[0032] The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0033] Such as figure 1 As shown, it is a schematic structural diagram of Embodiment 1 of the graphical interface automatic testing method of the present invention. The generated test part is mainly completed by QTP (Quicktest Professional). Generate data and images required by the entire system in QTP. The data processing part performs clustering and other processing on the data generated in QTP. The comparison result part accepts the clustering result, combined with manual marking, to determine the correctness of the image.

[0034] Such as figure 2 Shown is a schematic structural diagram of Embodiment 2 of the graphical interface automated testing method of the present invention.

[0035] The generated test part uses QTP to run scripts that randomly trigger software functions. The script automatically saves a ...

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Abstract

The invention relates to a graphic interface automated test method. The method comprises the following steps of automatically generating random test cases for to-be-tested software, generating records of operation sequences for function modules of test software, and storing a running screenshot; calculating the similarity between the operation sequences according to the records of the operation sequences, and giving out a matching relationship of operations in the operation sequences; clustering the operation sequences according to the similarity between the operation sequences; in each class, arbitrarily selecting one sequence and artificially marking right and wrong; in each class, performing image comparison on other similar sequences and the marked sequence; if comparison results are consistent, directly judging right and wrong, otherwise, regarding the sequence as an undetermined sequence; and if the undetermined sequence exists, returning to perform clustering. According to the method, similar operation sequences are subjected to image comparison in combination with OCR by applying an image comparison algorithm, and it is judged that function defects exist according to results or an iterative process is repeated; and the manual interventions are reduced by using machine learning and image comparison technologies, so that the test automation is realized and the software test efficiency is improved.

Description

technical field [0001] The invention relates to software testing technology, and the application of machine learning and image technology in automatic software testing. Background technique [0002] Currently, software testing generally requires a lot of human intervention. Test engineers need to design a large number of test cases, and most of the work is repetitive, tedious, and cumbersome; when the requirements or design changes, it is necessary to modify or redesign the test cases; and manual testing is difficult to completely cover the test scope, and it is necessary to repeat regression testing. Automating heavy testing tasks can improve the accuracy of testing and the enthusiasm of testers, expand the coverage of tests, free testers, and save personnel and time costs. [0003] Now there are many automatic testing tools, which can improve testing efficiency and replace manual input. They have functions such as recording scripts, playback, etc., and can reuse test ca...

Claims

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Application Information

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IPC IPC(8): G06F11/36
CPCG06F11/3684
Inventor 潘敏学黄嘉伟程成汤恩义
Owner NANJING UNIV
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