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Feature Matching-based Approaches to Improve the Robustness of Android visual gui testing

ACM TRANSACTIONS ON SOFTWARE ENGINEERING AND METHODOLOGY 2022年第2期31卷 1–32页

作者： Ardito, Luca Bottino, Andrea Coppola, Riccardo Lamberti, Fabrizio Manigrasso, Francesco Morra, Lia Torchiano, Marco Politecn Torino Corso Duca Abruzzi 29 I-10129 Turin Italy

In automated visual gui testing (VGT) for Android devices, the available tools often suffer from low robustness to mobile fragmentation, leading to incorrect results when running the same tests on different devices. To soften these issues, we evaluate two feature matching-based approaches for widget detection in VGT scripts, which use, respectively, the complete full-screen snapshot of the application (Fullscreen) and the cropped images of its widgets (Cropped) as visual locators to match on emulated devices. Our analysis includes validating the portability of different feature-based visual locators over various apps and devices and evaluating their robustness in terms of cross-device portability and correctly executed interactions. We assessed our results through a comparison with two state-of-the-art tools, EyeAutomate and Sikuli. Despite a limited increase in the computational burden, our Fullscreen approach outperformed state-ofthe-art tools in terms of correctly identified locators across a wide range of devices and led to a 30% increase in passing tests. Our work shows that VGT tools' dependability can be improved by bridging the testing and computer vision communities. This connection enables the design of algorithms targeted to domain-specific needs and thus inherently more usable and robust.

关键词： Mobile computing software testing visual gui testing feature matching

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A Failed attempt at creating guidelines for visual gui testing: An industrial case study 14

A Failed attempt at creating Guidelines for Visual GUI Testi...

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14th IEEE Conference on Software testing, Verification and Validation (ICST)

作者： Alegroth, Emil Petersen, Elin Tinnerholm, John Blekinge Inst Technol SERL Sweden Karlskrona Sweden Linkoping Univ Inst Comp Sci Linkoping Sweden

ISBN: (纸本)9781728168364

Software development is governed by guidelines that aim to improve the code's qualities, such as maintainability. However, whilst coding guidelines are commonplace for software, guidelines for testware are much less common. In particular, for gui-based tests driven with image recognition, also referred to as visual gui testing (VGT), explicit coding guidelines are missing. In this industrial case study, performed at the Swedish defence contractor Saab AB, we propose a set of coding guidelines for VGT and evaluate their impact on test scripts for an industrial, safety-critical system. To study the guidelines' effect on maintenance costs, five representative manual test cases are each translated with and without the proposed guidelines in the two VGT tools SikuliX and EyeAutomate. As such, 20 test scripts were developed, with a combined development cost of more than 100 man-hours. Three of the tests are then maintained by one researcher and two practitioners for another version of the system and costs measured to evaluate return on investment. This analysis is complemented with observations and interviews to elicit practitioners' perceptions and experiences with VGT. Results show that scripts developed with the guidelines had higher maintenance costs than scripts developed without guide-lines. This is supported by qualitative results that many of the guidelines are considered inappropriate, superfluous or unnecessary due to the inherent properties of the scripts, e.g. their natural small size, linear flows, natural separation of concerns, and more. We conclude that there are differences between VGT scripts and software that prohibit direct translation of guidelines between the two. As such, we consider our study as a failure but argue that several lessons can be drawn from our results to guide future research into guidelines for VGT and gui-based test automation.

关键词： Automated testing visual gui testing guidelines for testing Case study Industrial study

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Continuous Integration and visual gui testing: Benefits and Drawbacks in Industrial Practice 11

Continuous Integration and Visual GUI Testing: Benefits and ...

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11th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Alegroth, Emil Karlsson, Arvid Radway, Alexander Blekinge Inst Technol Dept Software Engn SE-37179 Karlskrona Sweden Cilbuper IT Johan Willins Gata 6 S-41664 Gothenburg Sweden Techship Krokslatts Fabriker 32 S-43137 Molndal Sweden

ISBN: (纸本)9781538650127

Continuous integration (CI) is growing in industrial popularity, spurred on by market trends towards faster delivery and higher quality software. A key facilitator of CI is automated testing that should be executed, automatically, on several levels of system abstraction. However, many systems lack the interfaces required for automated testing. Others lack test automation coverage of the system under test's (SUT) graphical user interface (gui) as it is shown to the user. One technique that shows promise to solve these challenges is visual gui testing (VGT), which uses image recognition to stimulate and assert the SUT's behavior. Research has presented the technique's applicability and feasibility in industry but only limited support, from an academic setting, that the technique is applicable in a CI environment. In this paper we presents a study from an industrial design research study with the objective to help bridge the gap in knowledge regarding VGT's applicability in a CI environment in industry. Results, acquired from interviews, observations and quantitative analysis of 17.567 test executions, collected over 16 weeks, show that VGT provides similar benefits to other automated test techniques for CI. However, several significant drawbacks, such as high costs, are also identified. The study concludes that, although VGT is applicable in an industrial CI environment, its severe challenges require more research and development before the technique becomes efficient in practice.

关键词： visual gui testing Continuous Integration Industrial Study Empirical Design Research

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Replicating Rare Software Failures with Exploratory visual gui testing

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IEEE SOFTWARE 2017年第5期34卷 53-59页

作者： Alegroth, Emil Gustafsson, Johan Ivarsson, Henrik Feldt, Robert Chalmers Univ Technol Software Engn Div Gothenburg Sweden Saab AB Stockholm Sweden Blekinge Inst Technol Karlskrona Sweden

Failure replication can be costly and tedious, especially for infrequent failures. Saab AB faced such a failure, which had persisted in their software for many years, until they developed a failure replication approac... 详细信息

关键词： Graphical User Interfaces Program testing Software Fault Tolerance Software Failure Replication visual gui testing Saab AB Developed Software Graphical User Interfaces Failure Analysis Companies Software Engineering visualization Memory Management visual gui testing Failure Replication Industrial Success Story Semiautomated testing Industry X 2013 Academia Collaboration Software Engineering Software Development Software testing Saab AB

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On the long-term use of visual gui testing in industrial practice: a case study

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EMPIRICAL SOFTWARE ENGINEERING 2017年第6期22卷 2937-2971页

作者： Alegroth, Emil Feldt, Robert Blekinge Inst Technol Dept Comp Sci & Engn SE-37179 Karlskrona Sweden Chalmers Univ Technol Dept Comp Sci & Engn SE-41296 Gothenburg Sweden

visual gui testing (VGT) is a tool-driven technique for automated gui-based testing that uses image recognition to interact with and assert the correctness of the behavior of a system through its gui as it is shown to the user. The technique's applicability, e.g. defect-finding ability, and feasibility, e.g. time to positive return on investment, have been shown through empirical studies in industrial practice. However, there is a lack of studies that evaluate the usefulness and challenges associated with VGT when used long-term (years) in industrial practice. This paper evaluates how VGT was adopted, applied and why it was abandoned at the music streaming application development company, Spotify, after several years of use. A qualitative study with two workshops and five well chosen employees is performed at the company, supported by a survey, which is analyzed with a grounded theory approach to answer the study's three research questions. The interviews provide insights into the challenges, problems and limitations, but also benefits, that Spotify experienced during the adoption and use of VGT. However, due to the technique's drawbacks, VGT has been abandoned for a new technique/framework, simply called the Test interface. The Test interface is considered more robust and flexible for Spotify's needs but has several drawbacks, including that it does not test the actual gui as shown to the user like VGT does. From the study's results it is concluded that VGT can be used long-term in industrial practice but it requires organizational change as well as engineering best practices to be beneficial. Through synthesis of the study's results, and results from previous work, a set of guidelines are presented that aim to aid practitioners to adopt and use VGT in industrial practice. However, due to the abandonment of the technique, future research is required to analyze in what types of projects the technique is, and is not, long-term viable. To this end, we also present Spo

关键词： Automated testing visual gui testing guidelines Industrial Case study

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Maintenance of automated test suites in industry: An empirical study on visual gui testing

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INFORMATION AND SOFTWARE TECHNOLOGY 2016年 73卷 66-80页

作者： Alegroth, Emil Feldt, Robert Kolstrom, Pirjo Chalmers Univ Technol Dept Comp Sci & Engn SE-41296 Gothenburg Sweden Blekinge Inst Technol Sch Comp Software Engn Res Lab SE-37179 Karlskrona Sweden Saab Sensis ATM Sweden Ljungadalsgatan 2 S-35246 Vaxjo Sweden

Context: Verification and validation (V&V) activities make up 20-50% of the total development costs of a software system in practice. Test automation is proposed to lower these V&V costs but available research only provides limited empirical data from industrial practice about the maintenance costs of automated tests and what factors affect these costs. In particular, these costs and factors are unknown for automated gui-based testing. Objective: This paper addresses this lack of knowledge through analysis of the costs and factors associated with the maintenance of automated gui-based tests in industrial practice. Method: An empirical study at two companies, Siemens and Saab, is reported where interviews about, and empirical work with, visual gui testing is performed to acquire data about the technique's maintenance costs and feasibility. Results: 13 factors are observed that affect maintenance, e.g. tester knowledge/experience and test case complexity. Further, statistical analysis shows that developing new test scripts is costlier than maintenance but also that frequent maintenance is less costly than infrequent, big bang maintenance. In addition a cost model, based on previous work, is presented that estimates the time to positive return on investment (ROI) of test automation compared to manual testing. Conclusions: It is concluded that test automation can lower overall software development costs of a project while also having positive effects on software quality. However, maintenance costs can still be considerable and the less time a company currently spends on manual testing, the more time is required before positive, economic, ROI is reached after automation. (C) 2016 Elsevier B.V. All rights reserved.

关键词： visual gui testing Maintenance Return on investment Empirical Industrial

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visual gui testing in practice: challenges, problemsand limitations

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EMPIRICAL SOFTWARE ENGINEERING 2015年第3期20卷 694-744页

作者： Alegroth, Emil Feldt, Robert Ryrholm, Lisa Chalmers Univ Technol Dept Comp Sci & Engn SE-41296 Gothenburg Sweden Univ Gothenburg SE-41296 Gothenburg Sweden Blekinge Inst Technol Dept Software Engn Karlskrona Sweden

In today's software development industry, high-level tests such as Graphical User Interface (gui) based system and acceptance tests are mostly performed with manual practices that are often costly, tedious and error prone. Test automation has been proposed to solve these problems but most automation techniques approach testing from a lower level of system abstraction. Their suitability for high-level tests has therefore been questioned. High-level test automation techniques such as Record and Replay exist, but studies suggest that these techniques suffer from limitations, e.g. sensitivity to gui layout or code changes, system implementation dependencies, etc. visual gui testing (VGT) is an emerging technique in industrial practice with perceived higher flexibility and robustness to certain gui changes than previous high-level (gui) test automation techniques. The core of VGT is image recognition which is applied to analyze and interact with the bitmap layer of a system's front end. By coupling image recognition with test scripts, VGT tools can emulate end user behavior on almost any gui-based system, regardless of implementation language, operating system or platform. However, VGT is not without its own challenges, problems and limitations (CPLs) but, like for many other automated test techniques, there is a lack of empirically-based knowledge of these CPLs and how they impact industrial applicability. Crucially, there is also a lack of information on the cost of applying this type of test automation in industry. This manuscript reports an empirical, multi-unit case study performed at two Swedish companies that develop safety-critical software. It studies their transition from manual system test cases into tests automated with VGT. In total, four different test suites that together include more than 300 high-level system test cases were automated for two multi-million lines of code systems. The results show that the transitioned test cases could find defects in the

关键词： visual gui testing Industrial case study Challenges Problems and Limitations System and acceptance test automation Development cost

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A real-time object detection method for electronic screen gui test systems

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JOURNAL OF SUPERCOMPUTING 2024年第15期80卷 22803-22835页

作者： Wang, Zhongmin Xi, Kang Gao, Cong Jin, Xiaomin Chen, Yanping Lu, Chen Xian Univ Posts & Telecommun Sch Comp Sci & Technol Xian 710121 Shaanxi Peoples R China Shaanxi Key Lab Network Data Anal & Intelligent Pr Xian 710121 Shaanxi Peoples R China Xian Key Lab Big Data & Intelligent Comp Xian 710121 Shaanxi Peoples R China Shenzhen Inst Informat Technol Shenzhen 518172 Guangdong Peoples R China

Automated testing of gui elements on electronic screens by machine vision is widely used in smart manufacturing production lines. However, in the complex environment of factories, interference factors such as light reflection, platform vibration, and placement angle make it difficult for testing robots to recognize and locate gui elements on the equipment's screen to be tested. In addition, the recognition algorithms based on screen gui elements currently have problems such as slow detection speed and large model size, which limit the deployment of detection models on test robots. To address these problems, this paper proposes a lightweight model that can overcome the interference of the factory environment based on the YOLOv5 algorithm for recognizing gui elements. First, a reinforced position and channel attention module (PCA) is proposed to enhance the extraction and fusion ability of weak feature elements affected by interference;then, a three-way feature pyramid network (TWFPN) module is constructed at the intermediate feature layer of the neck structure to provide more accurate localization information. Meanwhile, the loss function of the original algorithm is replaced with SIoU to improve the convergence speed. Finally, a lightweight structure combining the Ghost module and PConv is introduced into the model to reduce the model parameters and improve the detection speed. The method was evaluated on the constructed feature-enhanced gui (FE_gui) dataset. The final model shows a 2.7% improvement in average accuracy (mAP@0.5), a 30% reduction in model weight, and an increase in detection speed to 85 FPS compared to the original YOLOv5. The results demonstrate that the method solves the issues of element recognition and model deployment for a vision test system and surpasses existing models in terms of recognition accuracy and detection speed.

关键词： Machine vision Attention mechanism Lightweight model visual gui testing Graphical user interface

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Estimating Return on Investment for gui Test Automation Frameworks 30

Estimating Return on Investment for GUI Test Automation Fram...

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30th IEEE International Symposium on Software Reliability Engineering (ISSRE)

作者： Dobslaw, Felix Feldt, Robert Michaelsson, David Haar, Patrik Neto, Francisco G. de Oliveira Torkar, Richard Chalmers Univ Technol Dept Comp Sci & Engn Gothenburg Sweden Univ Gothenburg Canea Partner Grp Gothenburg Sweden Univ Gothenburg Dept Comp Sci & Engn Gothenburg Sweden

ISBN: (纸本)9781728149820

Automated graphical user interface (gui) tests can reduce manual testing activities and increase test frequency. This motivates the conversion of manual test cases into automated gui tests. However, it is not clear whether such automation is cost-effective given that gui automation scripts add to the code base and demand maintenance as a system evolves. In this paper, we introduce a method for estimating maintenance cost and Return on Investment (ROI) for Automated gui testing (AGT). The method utilizes the existing source code change history and has the potential to be used for the evaluation of other testing or quality assurance automation technologies. We evaluate the method for a real-world, industrial software system and compare two fundamentally different AGT frameworks, namely Selenium and EyeAutomate, to estimate and compare their ROI. We also report on their defect-finding capabilities and usability. The quantitative data is complemented by interviews with employees at the company the study has been conducted at. The method was successfully applied, and estimated maintenance cost and ROI for both frameworks are reported. Overall, the study supports earlier results showing that implementation time is the leading cost for introducing AGT. The findings further suggest that, while EyeAutomate tests are significantly faster to implement, Selenium tests require more of a programming background but less maintenance.

关键词： Test Automation Graphical User Interface visual gui testing Selenium EyeAutomate

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Automated gui testing: A Comparison Study With A Maintenance Focus

Automated GUI Testing: A Comparison Study With A Maintenance...

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作者： PATRIK HAAR University of Gothenburg

学位级别：硕士

Automated gui (Graphical User Interface) tests can alleviate work from testers, making it beneficial to convert manual test cases into automated gui tests. How- ever, automated gui tests come with costs and drawbacks not found in manual tests. These limitations can differ between automated gui testing tools. Two such tools are Selenium and EyeAutomate. The tools differ in their ways of locating gui components, with Selenium utilising underlying information about a web page and EyeAutomate relying on image recognition. For a practitioner deciding to adopt either tool, or similar ones, it is a benefit to know the strengths and weaknesses of them. This study has investigated general differences, implementation cost, maintenance cost, return on investment, and the defect-finding capabilities of Selenium and EyeAutomate. These properties were examined by subjecting tests written in each tool to system changes using version control history. Additional capabilities were determined by using manual fault injection. Qualitative data concerning the tools and automated gui testing were collected using interviews. Results indicate that while EyeAutomate tests are quicker to implement than Selenium tests, they require more time to maintain. Both tools have a similar return on investment, being able to reach it within one year compared to running a manual test suite weekly. The tools are comparable when finding defects during system development, with EyeAutomate being able to find more purely graphical related defects.

关键词： Software Engineering Automated gui testing Element-based testing visual gui testing Maintenance Return On Investment Fault Detection

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