GUI inspection from source code analysis

Graphical user interfaces (GUIs) are critical components of todays software. Given their increased relevance, correctness and usability of GUIs are becoming essential. This paper describes the latest results in the development of our tool to reverse engineer the GUI layer of interactive computing systems. We use static analysis techniques to generate models of the user interface behaviour from source code. Models help in graphical user interface inspection by allowing designers to concentrate on its more important aspects. One particularly type of model that the tool is able to generate is state machines. The paper shows how graph theory can be useful when applied to these models. A number of metrics and algorithms are used in the analysis of aspects of the user interface's quality. The ultimate goal of the tool is to enable analysis of interactive system through GUIs source code inspection.Fundação para a Ciência e a Tecnologia(PTDC/EIA-CCO/108995/2008

AN INVESTIGATION OF COMMON CODING ERRORS IN OPEN SOURCE GRAPHICAL USER INTERFACE CODE

Introduction: This thesis investigates the occurrence of coding errors in the Open Source Software (OSS) Graphical User Interface (GUI) code. Characteristics of coding errors in the OSS GUI code are explored and analyzed so that guidelines are proposed to lower the influence of coding errors in OSS GUI software. Background: This thesis recognizes the increased prominence of, as well as the increased total volume of OSS GUI code within modern software applications. This thesis seeks to identify whether specific types of errors manifest themselves more frequently in GUI code. The rationale behind this investigation is that: if specific errors are known to occur in specific locations then they can be more easily identified; if specific errors are due to specific causes then they can be more easily recognized in earlier stages of software development. Methods: Common coding errors were selected and examined in example OSS code using an automatic code inspection. An analysis of results from this inspection identified the frequency and location (i.e. in GUI or non-GUI code) of the common coding error. An initial sample of OSS GUI projects was selected to be examined and a wider range of OSS GUI projects was randomly chosen to evaluate the results that were obtained from the initial sample. Results: It was found that there are some differences in the type of errors within differing portions of source code. Certain types of coding errors were more frequently identified in GUI code than non-GUI code and corresponding typical GUI coding error-prone behaviors were summarized. Discussion: Awareness of these differences helps predict errors during the earlier stages of software development. Comprehension of these GUI coding error-prone behaviours contributes to prevent typical GUI coding errors as much as possible during the whole lifecycle of OSS GUI projects

Scripted GUI Testing of Android Apps: A Study on Diffusion, Evolution and Fragility

Background. Evidence suggests that mobile applications are not thoroughly tested as their desktop counterparts. In particular GUI testing is generally limited. Like web-based applications, mobile apps suffer from GUI test fragility, i.e. GUI test classes failing due to minor modifications in the GUI, without the application functionalities being altered. Aims. The objective of our study is to examine the diffusion of GUI testing on Android, and the amount of changes required to keep test classes up to date, and in particular the changes due to GUI test fragility. We define metrics to characterize the modifications and evolution of test classes and test methods, and proxies to estimate fragility-induced changes. Method. To perform our experiments, we selected six widely used open-source tools for scripted GUI testing of mobile applications previously described in the literature. We have mined the repositories on GitHub that used those tools, and computed our set of metrics. Results. We found that none of the considered GUI testing frameworks achieved a major diffusion among the open-source Android projects available on GitHub. For projects with GUI tests, we found that test suites have to be modified often, specifically 5\%-10\% of developers' modified LOCs belong to tests, and that a relevant portion (60\% on average) of such modifications are induced by fragility. Conclusions. Fragility of GUI test classes constitute a relevant concern, possibly being an obstacle for developers to adopt automated scripted GUI tests. This first evaluation and measure of fragility of Android scripted GUI testing can constitute a benchmark for developers, and the basis for the definition of a taxonomy of fragility causes, and actionable guidelines to mitigate the issue.Comment: PROMISE'17 Conference, Best Paper Awar

NEFI: Network Extraction From Images

Networks and network-like structures are amongst the central building blocks of many technological and biological systems. Given a mathematical graph representation of a network, methods from graph theory enable a precise investigation of its properties. Software for the analysis of graphs is widely available and has been applied to graphs describing large scale networks such as social networks, protein-interaction networks, etc. In these applications, graph acquisition, i.e., the extraction of a mathematical graph from a network, is relatively simple. However, for many network-like structures, e.g. leaf venations, slime molds and mud cracks, data collection relies on images where graph extraction requires domain-specific solutions or even manual. Here we introduce Network Extraction From Images, NEFI, a software tool that automatically extracts accurate graphs from images of a wide range of networks originating in various domains. While there is previous work on graph extraction from images, theoretical results are fully accessible only to an expert audience and ready-to-use implementations for non-experts are rarely available or insufficiently documented. NEFI provides a novel platform allowing practitioners from many disciplines to easily extract graph representations from images by supplying flexible tools from image processing, computer vision and graph theory bundled in a convenient package. Thus, NEFI constitutes a scalable alternative to tedious and error-prone manual graph extraction and special purpose tools. We anticipate NEFI to enable the collection of larger datasets by reducing the time spent on graph extraction. The analysis of these new datasets may open up the possibility to gain new insights into the structure and function of various types of networks. NEFI is open source and available http://nefi.mpi-inf.mpg.de

Using High-Rising Cities to Visualize Performance in Real-Time

For developers concerned with a performance drop or improvement in their software, a profiler allows a developer to quickly search and identify bottlenecks and leaks that consume much execution time. Non real-time profilers analyze the history of already executed stack traces, while a real-time profiler outputs the results concurrently with the execution of software, so users can know the results instantaneously. However, a real-time profiler risks providing overly large and complex outputs, which is difficult for developers to quickly analyze. In this paper, we visualize the performance data from a real-time profiler. We visualize program execution as a three-dimensional (3D) city, representing the structure of the program as artifacts in a city (i.e., classes and packages expressed as buildings and districts) and their program executions expressed as the fluctuating height of artifacts. Through two case studies and using a prototype of our proposed visualization, we demonstrate how our visualization can easily identify performance issues such as a memory leak and compare performance changes between versions of a program. A demonstration of the interactive features of our prototype is available at https://youtu.be/eleVo19Hp4k.Comment: 10 pages, VISSOFT 2017, Artifact: https://github.com/sefield/high-rising-city-artifac

The Dag-Brucken ASRS Case Study

In 1996 an agreement was made between a well-known beverage manufacturer, Super-Cola Taiwan, (SCT) and a small Australian electrical engineering company, Dag-Brücken ASRS Pty Ltd, (DB), to provide an automated storage and retrieval system (ASRS) facility as part of SCT’s production facilities in Asia. Recognising the potential of their innovative and technically advanced design, DB was awarded a State Premiers Export Award and was a finalist in that year’s National Export Awards. The case tracks the development and subsequent implementation of the SCT ASRS project, setting out to highlight how the lack of appropriate IT development processes contributed to the ultimate failure of the project and the subsequent winding up of DB only one year after being honoured with these prestigious awards. The case provides compelling evidence of the types of project management incompetency that, from the literature, appears to contribute to the high failure rate in IT projects. For confidentiality reasons, the names of the principal parties are changed, but the case covers actual events documented by one of the project team members as part of his postgraduate studies, providing an example of the special mode of evidence collection that Yin (1994) calls ‘participant-observation’