Abstract
Graphical user interfaces (GUIs) make software easy to use by providing the user with visual controls. Therefore, correctness of GUI's code is essential to the correct execution of the overall software. Models can help in the evaluation of interactive applications by allowing designers to concentrate on its more important aspects. This paper presents a generic model for language-independent reverse engineering of graphical user interface based applications, and we explore the integration of model-based testing techniques in our approach, thus allowing us to perform fault detection. A prototype tool has been constructed, which is already capable of deriving and testing a user interface behavioral model of applications written in Java/Swing. Copyright 2009 ACM.

Abstract
This document presents the case study for the ABZ 2023 conference. The case study introduces a safety critical interactive system called AMAN (Arrival MANager), which is a partly-autonomous scheduler of landing sequences of aircraft in airports. This interactive systems interleaves Air Traffic Controllers activities with automation in AMAN. While some AMAN systems are currently deployed in airports, we consider here only a subset of functions which represent a challenge in modelling and verification. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
This second workshop on HCI Engineering Education aims at carrying forward work on identifying, examining, structuring, and sharing educational resources and approaches to support the process of teaching/learning Human-Computer Interaction (HCI) Engineering. The widening range of available interaction technologies and their applications in increasingly varied contexts (private or professional) underlines the importance of teaching HCI Engineering but also the difficulty of taking into account changes and developments in this field in often static university curricula. Besides, as these technologies are taught in diverse curricula (ranging from Human Factors and Psychology to hardcore Computer Science), we are interested in what the best approaches and best practices are to integrate HCI Engineering topics in the curricula of programs in Software Engineering, Computer Science, Human-computer Interaction, Psychology, Design, etc. The workshop is proposed on behalf of the IFIP Working Group 2.7/13.4 on User Interface Engineering. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
The IVY workbench is a model-based tool for the formal modelling and verification of interactive systems. The tool uses model checking to carry out the verification step. The goal is not to replace, but to complement more exploratory and iterative user-centred design approaches. However, the need for formal and rigorous modelling and reasoning raises challenges for the integration of both approaches. This paper presents a new plugin that aims to provide support for the integration of the formal methods based analysis supported by the tool, with user-centred design. The plugin is described, and an initial validation of its functionalities presented. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Slight variations in user interface response times can significantly impact the user experience provided by an interface. Load testing is used to evaluate how an application behaves under increasing loads. For interactive applications, load testing can be done by directly calling services at the business logic or through the user interface. In modern web applications, there is a considerable amount of control logic on the browser side. The impact of this logic on applications’ behaviour is only fully considered if the tests are done through the user interface. Capture reply tools are used for this, but their use can become costly. Leveraging an existing model-based testing tool, we propose an approach to automate load testing done through the user interface. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Abstract
Background: Many programming environments include automated feedback in the form of hints to help novices learn autonomously. Some experimental studies investigated the impact of automated hints in the immediate performance and learning retention in that context. Automated feedback is also becoming a popular research topic in the context of formal specification languages, but so far no experimental studies have been conducted to assess its impact while learning such languages. Objective: We aim to investigate the impact of different types of automated hints while learning a formal specification language, not only in terms of immediate performance and learning retention, but also in the emotional response of the students. Method: We conducted a simple one-factor randomised experiment in 2 sessions involving 85 BSc students majoring in CSE. In the 1st session students were divided in 1 control group and 3 experimental groups, each receiving a different type of hint while learning to specify simple requirements with the Alloy formal specification language. To assess the impact of hints on learning retention, in the 2nd session, 1 week later, students had no hints while formalising requirements. Before and after each session the students answered a standard self-reporting emotional survey to assess their emotional response to the experiment. Results: Of the 3 types of hints considered, only those pointing to the precise location of an error had a positive impact on the immediate performance and none had significant impact in learning retention. Hint availability also causes a significant impact on the emotional response, but no significant emotional impact exists once hints are no longer available (i.e. no deprivation effects were detected). Conclusion: Although none of the evaluated hints had an impact on learning retention, learning a formal specification language with an environment that provides hints with precise error locations seems to contribute to a better overall experience without apparent drawbacks. Further studies are needed to investigate if other kind of feedback, namely hints combined with some sort of self-explanation prompts, can have a positive impact in learning retention. © 2024 Copyright held by the owner/author(s).