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Title:
Automatic GUI Test by Using SIFT Matching
Author: Fang, XX ; Sheng, B ; Li, P ; Wu, D ; Wu, EH
Keyword: GUI test ; image recognition ; SIFT ; random fern
Source: CHINA COMMUNICATIONS
Issued Date: 2016
Volume: 13, Issue:9, Pages:227-236
Indexed Type: SCI
Department: Shanghai Jiao Tong Univ, Dept Comp Sci & Engn, Shanghai 200240, Peoples R China. Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100190, Peoples R China. Educ Univ Hong Kong, Dept Math & Informat Technol, Hong Kong, Hong Kong, Peoples R China. China Southern Power Grid, Dept Informat, Guangzhou, Guangdong, Peoples R China. Univ Macau, Fac Sci & Technol, Macau, Peoples R China.
Abstract: In software development process, the last step is usually the Graphic User Interface(GUI) test, which is part of the final user experience (UE) test. Traditionally, there exist some GUI test tools in the market, such as Abbot Java GUI Test Framework and Pounder, in which testers pre-configure in the script all desired actions and instructions for the computer, nonetheless requiring too much of invariance of GUI environment; and they require reconfiguration in case of GUI changes, therefore still to be done mostly manually and hard for non-programmer testers to. Consequently, we proposed GUI tests by image recognition to automate the last process; we managed to innovate upon current algorithms such as SIFT and Random Fern, from which we develop the new algorithm scheme retrieving most efficient feature and dispelling inefficient part of each algorithm. Computers then apply the algorithm, to search for target patterns themselves and take subsequent actions such as manual mouse, keyboard and screen I/O automatically to test the GUI without any manual instructions. Test results showed that the proposed approach can accelerate GUI test largely compared to current benchmarks.
English Abstract: In software development process, the last step is usually the Graphic User Interface(GUI) test, which is part of the final user experience (UE) test. Traditionally, there exist some GUI test tools in the market, such as Abbot Java GUI Test Framework and Pounder, in which testers pre-configure in the script all desired actions and instructions for the computer, nonetheless requiring too much of invariance of GUI environment; and they require reconfiguration in case of GUI changes, therefore still to be done mostly manually and hard for non-programmer testers to. Consequently, we proposed GUI tests by image recognition to automate the last process; we managed to innovate upon current algorithms such as SIFT and Random Fern, from which we develop the new algorithm scheme retrieving most efficient feature and dispelling inefficient part of each algorithm. Computers then apply the algorithm, to search for target patterns themselves and take subsequent actions such as manual mouse, keyboard and screen I/O automatically to test the GUI without any manual instructions. Test results showed that the proposed approach can accelerate GUI test largely compared to current benchmarks.
Language: 英语
WOS ID: WOS:000383938000024
Citation statistics:
Content Type: 期刊论文
URI: http://ir.iscas.ac.cn/handle/311060/17308
Appears in Collections:软件所图书馆_期刊论文

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Recommended Citation:
Fang, XX,Sheng, B,Li, P,et al. Automatic GUI Test by Using SIFT Matching[J]. CHINA COMMUNICATIONS,2016-01-01,13(9):227-236.
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