GUI testing assisted by human knowledge: Random vs. functional

Yang, Weiran; Chen, Zhenyu; Gao, Zebao; Zou, Yunxiao; Xu, Xiaoran

doi:10.1016/j.jss.2013.09.043

Cited by 9 publications

(8 citation statements)

References 9 publications

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“…Model‐based testing approaches() use a UI model that is derived from the app GUI either manually or dynamically during app exercising. Generally, model‐based testing is the most suitable mechanism for guiding automated UI testing and is usually combined with random testing or dynamic symbolic execution.…”

Section: Related Workmentioning

confidence: 99%

“…A central challenge in automated testing is the generation of tests with high coverage due to the highly interactive nature of the app graphical user interfaces (GUIs). 1,2 In addition, existing GUI testing techniques [3][4][5][6] for the automated testing of PC-based applications are no longer feasible to perform GUI testing of mobile apps due to their specific nontrivial GUI structure. 2,7 Consequently, in recent years, many automated GUI testing systems for mobile apps have been developed.…”

Section: Introductionmentioning

confidence: 99%

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Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation

et al. 2018

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Summary The increasingly prevalent use of mobile devices has raised the popularity of mobile applications. Therefore, automated testing of mobile applications has become an extremely important task. However, it is still a challenge to automatically generate tests with high coverage for mobile applications due to their specific nontrivial structure and the highly interactive nature of graphical user interfaces (GUIs). In this paper, we propose a novel automated GUI testing technique for mobile applications, namely, Mobolic. In this approach, tests with high coverage are automatically generated and executed by combining the online testing technique and customated input generation. Employing the online testing technique, Mobolic systematically explores the app GUI without falling in a loop. It generates relevant events “on the fly” that are followed by an immediate execution. In addition, involving the customated input generation, Mobolic automatically generates relevant user inputs such as user‐predefined, concrete, or random ones. We implemented Mobolic and evaluated its performance on 10 real‐world open‐source Android applications. Our experimental results show the effectiveness and efficiency of Mobolic in terms of achieved code coverage and overall exercising time.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation

et al. 2018

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“…Yang et al [27] study the difference between random testing and functional testing in GUI applications. They show the importance of human knowledge in testing large applications via creating more meaningful functional tests.…”

Section: Related Workmentioning

confidence: 99%

“…repairedSeg [26][27][28]. Second, the event may still exist in A 1 , but may have been missed during automatic creation of G 1 .…”

Section: Repairingmentioning

confidence: 99%

SITAR: GUI Test Script Repair

Gao

Chen

Zou

et al. 2016

IIEEE Trans. Software Eng.

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System testing of a GUI-based application requires that test cases, consisting of sequences of user actions/events, be executed and the software's output be verified. To enable automated re-testing, such test cases are increasingly being coded as low-level test scripts, to be replayed automatically using test harnesses. Whenever the GUI changes-widgets get moved around, windows get merged-some scripts become unusable because they no longer encode valid input sequences. Moreover, because the software's output may have changed, their test oracles-assertions and checkpoints-encoded in the scripts may no longer correctly check the intended GUI objects. We present ScrIpT repAireR (SITAR), a technique to automatically repair unusable low-level test scripts. SITAR uses reverse engineering techniques to create an abstract test for each script, maps it to an annotated event-flow graph (EFG), uses repairing transformations and human input to repair the test, and synthesizes a new "repaired" test script. During this process, SITAR also repairs the reference to the GUI objects used in the checkpoints yielding a final test script that can be executed automatically to validate the revised software. SITAR amortizes the cost of human intervention across multiple scripts by accumulating the human knowledge as annotations on the EFG. An experiment using QTP test scripts suggests that SITAR is effective in that 41-89% unusable test scripts were repaired. Annotations significantly reduced human cost after 20% test scripts had been repaired.

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“…After discussing with teacher and TAs, the undergraduate students conduct the empirical study and completed a paper [8]. We study three aspects on these two testing strategies: effectiveness, complementarity and the impact of test case length.…”

Section: Successful Experiencesmentioning

confidence: 99%

Combining research and education of software testing

Chen

Memon

Luo

2014

Proceedings of the 29th Annual ACM Symposium on Applied Computing

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This paper reports a preliminary study on combining research and education of software testing. We introduce some industrial-strength programs, from the open-source projects for research, into the assignments of system testing. Research assistants and teaching assistants work together to establish and evaluate the assignments of system testing. Our preliminary results show that research and education of software testing can benefit each other in this way.

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GUI testing assisted by human knowledge: Random vs. functional

Cited by 9 publications

References 9 publications

Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation

Mobolic: An automated approach to exercising mobile application GUIs using symbiosis of online testing technique and customated input generation

SITAR: GUI Test Script Repair

Combining research and education of software testing

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