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16th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Ricos, Fernando Pastor Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9783031057601;9783031057595

Extended Reality (XR) systems are complex applications that have emerged in a wide variety of domains, such as computer games and medical practice. testing XR software is mainly done manually by human testers, which implies a high cost in terms of time and money. Current automated testing approaches for XR systems consist of rudimentary capture and replay of scripts. However, this approach only works for simple test scenarios. Moreover, it is well-known that the scripts break easily each time the XR system is changed. There are research projects aimed at using autonomous agents that will follow scripted instructions to test XR functionalities. Nonetheless, using only scripted testing techniques, it is difficult and expensive to tackle the challenges of testing XR systems. This thesis is focus on the use of automated scriptless testing for XR systems. This way we help to reduce part of the manual testing effort and complement the scripted techniques.

关键词： scriptless testing State model inference Extended reality

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Novelty-Driven Evolutionary scriptless testing 18th

Novelty-Driven Evolutionary Scriptless Testing

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18th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Hufkens, Lianne V. Vos, Tanja E. J. Marin, Beatriz Open Univ Valkenburgerweg 177 NL-6419 AT Heerlen Netherlands Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9783031594670;9783031594687

In recent years, scriptless Graphical User Interface (GUI) testing has been positioned as a complement to traditional testing techniques. Automated scriptless GUI testing approaches use Action Selection Rules (ASR) to generate on-the-fly test sequences when testing a software system. Currently, random is the standard selection approach in scriptless testing, provoking drawbacks in the testing process, such as test sequences that do not reflect the human strategies for testing, and being unable to deal with multistep tasks. This paper presents an alternate selection approach based on the use of a grammar to design the ASR and an Evolutionary Algorithm (EA) with Novelty Search (NS) to direct the evolution process. Preliminary testing shows that the ASRS do evolve in the standard EA process. Further research is needed to show the benefits of the additional NS for the testing process.

关键词： Automated GUI testing scriptless testing Novelty Search Grammar-based testing Evolutionary testing Grammatical Evolution

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Grammar-Based Action Selection Rules for scriptless testing 5

Grammar-Based Action Selection Rules for Scriptless Testing

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5th IEEE/ACM International Conference on Automation of Software Test (AST)

作者： Hufkens, Lianne V. Pastor Ricos, Fernando Marin, Beatriz Vos, Tanja E. J. Open Univ Heerlen Netherlands Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9798400705885

scriptless testing at the GUI level involves generating test sequences on the fly. These test sequences mimic user interactions on the GUI. The creation of these sequences works through action selection rules, which is most commonly based on stochastic methods. scriptless tests are reliable because they work with the actual state of the System Under Test (SUT). However, the tests are less specific, harder to interpret, and it is difficult to test concrete use cases or workflows. We want to tackle this drawback of scriptless tests by introducing action selection rules that are easier to guide than pure stochastic methods. In this paper, a new approach based on a grammar for the action selection rules is proposed, enabling scriptless testing tools to mimic user behaviour when interacting with web applications. While grammars have been used in software testing to generate input data for test cases, the proposed approach uses grammars to specify action selection rules to generate test sequences that mimic testing strategies employed by human testers. An empirical study has been performed to evaluate the effectiveness and the efficiency of the grammar-based action selection rules to filing web forms in comparison with random action selection rules. In the study, two SUTs were used: WebformSUT and Parabank. The average success rate for the grammar-based approach was 95.9% against random's 57.0% for WebformSUT and 99.8% against 55.7% for Parabank. For the widget interaction grammar-based had an average deviation from the ideal ratio of 0.06165 (WebformSUT) and 0.0180 (Parabank), compared random's 0.4318 (WebformSUT) and 0.7774 (Parabank). The results demonstrate the effectiveness of the grammar-based approach and the improvement in the use of resources.

关键词： GUI testing scriptless testing action selection grammars

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Evolutionary scriptless testing 16th

Evolutionary Scriptless Testing

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16th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Hufkens, Lianne Valerie Open Univ Heerlen Netherlands

ISBN: (纸本)9783031057601;9783031057595

Automated scriptless testing approaches use Action Selection Rules (ASR) to generate on-the-fly test sequences when testing a software system. Currently, these rules are manually designed and implemented. In this paper we present our research on how to automatically create ASRs by evolving them using an evolutionary algorithm. Expected results are an automated system for Evolutionary scriptless testing containing a representation of ASRs, different fitness functions and manipulation operators.

关键词： Automated GUI testing scriptless testing Evolutionary testing

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Automated scriptless GUI testing Aligned with Requirements and User Stories 18th

Automated Scriptless GUI Testing Aligned with Requirements a...

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18th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Karimi, Mohammadparsa Open Univ Heerlen Netherlands

ISBN: (纸本)9783031594670;9783031594687

testing is an essential phase of software development to evaluate the quality of the product. scriptless testing is a prominent technique that makes this phase efficient. However, there is a research gap in automating the testing process from the requirements. In this research we want to propose an innovative approach: Automated scriptless GUI testing Aligned with Requirements and User Stories. Using the open-source GUI testing tool, TESTAR, we want to propose an AI-powered tool that enables TESTAR to test software against specified requirements and user stories.

关键词： GUI testing scriptless testing Requirements testing

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Distributed state model inference for scriptless GUI testing

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JOURNAL OF SYSTEMS AND SOFTWARE 2023年 200卷

作者： Ricos, Fernando Pastor Slomp, Arend Marin, Beatriz Aho, Pekka Vos, Tanja E. J. Univ Politecn Valencia Valencia Spain Open Univ Heerlen Netherlands

State model inference of software applications through the Graphical User Interface (GUI) is a technique that identifies GUI states and transitions, and maps them into a model. scriptless GUI testing tools can benefit substantially from the availability of these state models, for example, to improve the exploration, or have sophisticated test oracles. However, inferring models for large systems requires a long execution time. Our goal is to improve the speed of the state model inference process. To achieve this goal, this paper presents a distributed state model inference approach with an open source scriptless GUI testing tool. Moreover, in order to be able to infer a suitable model, we design a set of strategies to deal with abstraction challenges and to distinguish GUI states and transitions in the model. To validate it, we conduct an experiment with two open source web applications that have been tested with the distributed architecture using one to six Docker containers sharing the same state model. With the obtained results, we can conclude that it is feasible to infer a model with a distributed approach and that using the distributed approach reduces the time required for inferring a state model.(c) 2023 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://***/licenses/by/4.0/).

关键词： Distributed systems scriptless testing State model inference Empirical evaluation

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Scripted and scriptless GUI testing for web applications: An industrial case

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INFORMATION AND SOFTWARE TECHNOLOGY 2023年第1期158卷

作者： Bons, Axel Marin, Beatriz Aho, Pekka Vos, Tanja E. J. Open Univ Heerlen Netherlands Univ Politecn Valencia Valencia Spain

Context: Automation is required in the software development to reduce the high costs of producing software and to address the short release cycles of modern development processes. Lot of effort has been performed to automate testing, which is one of the most resource-consuming development phases. Automation of testing through the Graphical User Interface (GUI) has been researched to improve the system ***: We aim to evaluate the complementarity of automated GUI testing tools in a real industrial context, which refers to the capability of the tools to work usefully ***: To address the objective, we conduct an exploratory case study in an IT development company from The Netherlands. We select two representative tools for automated GUI testing, one for scripted and another for scriptless testing. We measure the complementarity by measuring the effectiveness, the efficiency, and subjective satisfaction of the tools. Results: It can be observed that the scripted tool performs better in detecting process failures, and the scriptless tool performs better in detecting visible failures and also reaching higher coverage. Both tools perform in a similar way in terms of efficiency. Additionally, both tools were perceived to be useful in the survey performed for the subjective ***: We conclude that scriptless and scripted testing approaches are complementary, and they can improve the effectiveness compared to manual testing processes performed in an industrial context by detecting different failures and reducing the effort and time to find these failures and to reproduce them.

关键词： Case study Complementarity scriptless testing Scripted testing

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scriptless and Seamless: Leveraging Probabilistic Models for Enhanced GUI testing in Native Android Applications 18th

Scriptless and Seamless: Leveraging Probabilistic Models for...

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18th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Rodriguez-Valdes, Olivia van der Vlist, Kevin van Dalen, Robbert Marin, Beatriz Vos, Tanja E. J. ING Bank Amsterdam Netherlands Univ Politecn Valencia Valencia Spain Open Univ Heerlen Netherlands

ISBN: (纸本)9783031594670;9783031594687

The growing mobile app market demands effective testing methods. scriptless testing at the Graphical User Interface (GUI) level allows test automation without traditional scripting. Nevertheless, existent scriptless tools lack efficient prioritization and customization of oracles and require manual effort to add application-specific context, hindering rapid application releases. This paper presents Mint as an alternative tool that addresses these drawbacks. Preliminary results indicate its capability to detect accessibility problems.

关键词： Mobile apps test automation scriptless testing accessibility oracle

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Delta GUI change detection using inferred models

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COMPUTER STANDARDS & INTERFACES 2025年 92卷

作者： Ricos, Fernando Pastor Marin, Beatriz Vos, Tanja E. J. Neeft, Rick Aho, Pekka Univ Politecn Valencia Valencia Spain Open Univ Heerlen Netherlands

Recent software development methodologies emphasize iterative and incremental evolution to align with stakeholders' needs. This perpetual and rapid software evolution demands ongoing research into verification practices and technologies that ensure swift responsiveness and effective management of software delta increments. Strategies such as code review have been widely adopted for development and verification, ensuring readability and consistency in the delta increments of software projects. However, the integration of techniques to detect and visually report delta changes within the Graphical User Interface (GUI) software applications remains an underutilized process. In this paper, we set out to achieve two objectives. First, we aim to conduct a comprehensive review of existing studies concerning GUI change detection in desktop, web, and mobile applications to recognize common practices. Second, we introduce a novel change detection tool capable of highlighting delta GUI changes for this diverse range of applications. To accomplish our first objective, we performed a systematic mapping of the literature using the Scopus database. To address the second objective, we designed and developed a GUI change detection tool. This tool simultaneously transits and compares state models inferred by a scriptless testing tool, enabling the detection and highlighting of GUI changes to detect the widgets or functionalities that have been added, removed, or modified. Our study reveals the existence of a multitude of techniques for change detection in specific GUI systems with different objectives. However, there is no widely adopted technique suitable for the diverse range of existing desktop, web, and mobile applications. Our tool and findings demonstrate the effectiveness of using inferred state models to highlight between 8 and 20 GUI changes in software delta increments containing a large number of changes over months and between 4 and 6 GUI changes in delta increments of sma

关键词： Delta validation GUI change detection scriptless testing State model inference Systematic mapping

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Towards a testing tool that learns to test 21

Towards a testing tool that learns to test

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IEEE/ACM 43rd International Conference on Software Engineering (ICSE)

作者： Rodriguez-Valdes, Olivia Open Univ Heerlen Netherlands

ISBN: (纸本)9781665412193

We will study the application of Reinforcement Learning techniques in automated GUI testing. Using the scriptless GUI testing tool TESTAR as a vehicle, we will focus our research on improving the action selection mechanisms, that guide the learning process. We will tailor rewards towards the goal of enhancing the effectiveness and efficiency of testing.

关键词： scriptless testing Reinforcement Learning GUI testing

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