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 testing. 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 together. 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. 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 satisfaction. 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.

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.

Traditionally, end-to-end testing of mobile apps is either performed manually or automated with test scripts. However, manual GUI testing is expensive and slow, and test scripts are fragile for GUI changes, resulting in high maintenance costs. Scriptless testing attempts to address the costs associated with GUI testing. Existing scriptless approaches for mobile testing do not seem to fit the requirements of the industry, specifically those of the ING. This study presents an extension to open source TESTAR tool to support scriptless GUI testing of Android and iOS applications. We present an initial validation of the tool on an industrial setting at the ING. From the validation, we determine that the extended TESTAR outperforms two other state-of-the-art scriptless testing tools for Android in terms of code coverage, and achieves similar performance as the scripted test automation already in use at the ING. Moreover, we see that the scriptless approach covers parts of the application under test that the existing test scripts did not cover, showing the complementarity of the approaches, providing more value for the testers.

Summary Covering all the possible paths of the graphical user interface (GUI) with test scripts would take too much effort and result in serious maintenance issues. We propose complementing scripted testing with scriptless test automation using the open‐source testar tool. This paper gives a comprehensive overview of testar and its latest extensions together with the ongoing and future research. With this paper, we hope we can help and encourage other researchers to use testar for their GUI testing‐related research and pave the way for an international research agenda in GUI testing built upon stable and open‐source infrastructure.

Model-driven development (MDD) aims to increase productivity in software development and manage the complexity of software by utilizing modelling to shift from programming in solution-space to modelling in problem-space. Another approach to increase productivity and experience significant cost savings is to utilize open source (OS) components in software development. This paper presents the state of the art of how to combine MDD methods with OS software development. The approach is called open models software development which is expected to combine the benefits of both worlds. The fundamental idea of open models development is to apply community-driven collaborative MDD. In this paper, open models development is exemplified by constructing resource availability service (RAS). RAS is a web service for providing availability information about resources such as services, content, users and terminals. This paper shows that Open Models development is feasible from technical point of view although there are still great challenges in tooling. In addition, more empirical research is needed in studying attractiveness of open models.