Creating GUI testing tools using accessibility technologies

Abstract Since manual black-box testing of GUI-based APplications (GAPs

Automated blackbox GUI specifications enhancement and test data generation

Applications with a Graphical User Interface (GUI) front-end are ubiquitous nowadays. While automated model-based approaches have been shown to be effective in testing of such applications, most existing techniques produce many infeasible event sequences used as GUI test cases. This happens primarily because the behavioral specifications of the GUI under test are ignored. In this dissertation we present an automated framework that reveals an important set of state-based constraints among GUI events based on infeasible (i.e., unexecutable or partially executable) test cases of a GUI test suite. GUIDiVa, an iterative algorithm at the core of our framework, enumerates all possible constraint violations as potential reasons for test case failure, on the failed event of an infeasible test case. It then selects and adds the most promising constraints of each iteration to a final set based on the Validity Weight of constraints. The results of empirical studies on both seeded and nine non-trivial open-source study subjects show that our framework is capable of capturing important aspects of GUI behavior in the form of state-based event constraints, while considerably reducing the number of insfeasible test cases. The second part of this dissertation deals with the problem of automatic generation of relevant test data for parameterized GUI events (i.e., events associated with widgets that accept user inputs such as textboxes and textareas). Current techniques either manipulate the source code of the application under test (AUT) to generate the test data, or blindly use a set of random string values. We propose a novel way to generate the test data by exploiting the information provided in the GUI structure to extract a set of key identifiers for each parameterized GUI widget. These identifiers are used to compose appropriate online search phrases and collect relevant test data from the Internet. The results of an empirical study on five GUI-based applications show that the proposed approach is applicable and results in execution of some hard-to-cover branches in the subject programs. The proposed technique works from a black-box perspective and is entirely independent from GUI modeling and event sequence generation, thus it does not require source code access and offers the possibility of being integrated with existing GUI testing frameworks

A Regression Test Selection Technique for Graphical User Interfaces

Regression testing is a quality control measure to ensure that the newly modified part of the software still complies with its specified requirements and that the unmodified part has not been affected by the maintenance activity. Regression testing is an important and expensive activity during the software maintenance process and its purpose is to ensure quality and reliability in modified software. Regression testing selection techniques are focused on the reusability of existing test suites for a modified program from a previous version. Many regression testing selection techniques have been approached for conventional and object-oriented software. There is little discussion about those techniques to be applied for the Graphical User Interfaces (GUIs). This thesis addresses the gap. GUIs have characteristics different from traditional software, and the conventional testing techniques do not directly apply to GUIs. Unlike most previous techniques for selective retest, this thesis focuses on developing an event driven regression testing selection technique for GUIs. It defines an event dependence graph (EDG) to identify the interaction and relationship of the events within GUI components, develops an algorithm to construct the EDG for GUIs, and presents the GUI modeling structure and its selection retest technique. An algorithm is given to determine and generate a modified test suite automatically for GUI based on its original version. Experiments are presented on an implementation of this solution and discusses newly found challenges when applied to an established GUI application. Finally, feasibility and future areas of research are addressed on the findings during the implementation of the solution

Defining and Evaluating Test Suite Consolidation for Event Sequence-based Test Cases

This research presents a new test suite consolidation technique, called CONTEST, for automated GUI testing. A new probabilistic model of the GUI is developed to allow direct application of CONTEST. Multiple existing test suites are used to populate the model and compute probabilities based on the observed event sequences. These probabilities are used to generate a new test suite that consolidates the original ones. A new test suite similarity metric, called CONTeSSi(n), is introduced which compares multiple event sequence-based test suites using relative event positions. Results of empirical studies showed that CONTEST yields a test suite that achieves better fault detection and code coverage than the original suites, and that the CONTeSSi(n) metric is a better indicator of the similarity between sequence-based test suites than existing metrics

Reverse Engineering and Testing of Rich Internet Applications

The World Wide Web experiences a continuous and constant evolution, where new initiatives, standards, approaches and technologies are continuously proposed for developing more effective and higher quality Web applications. To satisfy the growing request of the market for Web applications, new technologies, frameworks, tools and environments that allow to develop Web and mobile applications with the least effort and in very short time have been introduced in the last years. These new technologies have made possible the dawn of a new generation of Web applications, named Rich Internet Applications (RIAs), that offer greater usability and interactivity than traditional ones. This evolution has been accompanied by some drawbacks that are mostly due to the lack of applying well-known software engineering practices and approaches. As a consequence, new research questions and challenges have emerged in the field of web and mobile applications maintenance and testing. The research activity described in this thesis has addressed some of these topics with the specific aim of proposing new and effective solutions to the problems of modelling, reverse engineering, comprehending, re-documenting and testing existing RIAs. Due to the growing relevance of mobile applications in the renewed Web scenarios, the problem of testing mobile applications developed for the Android operating system has been addressed too, in an attempt of exploring and proposing new techniques of testing automation for these type of applications

Feedback-Directed Model-Based GUI Test Case Generation

Most of today's software users interact with the software through a graphical user interfac (GUI), which is a representative of the broader class of event-driven software (EDS). As the correctness of the GUI is necessary to ensure the correctness of the overall software, its quality assurance (QA) is becoming increasingly important. During software testing, an important QA technique, test cases are created and executed on the software. For GUIs, test cases are modeled as sequences of user input events. Because each possible sequence of user events may potentially be a test case and because today's GUIs offer enormous flexibility to end users, in principle, GUI testing requires a prohibitively large number of test cases. Any practical test case generation technique must sample the vast GUI input space. Existing techniques are either extremely resource intensive or do not adequately model complex GUI behaviors, thereby limiting fault detection. This research develops new models, algorithms, and metrics for automated GUI test case generation. A novel aspect of this work is its use of software runtime information collected as feedback during GUI test case execution, and used to generate additional test cases that model complex GUI behaviors. One set of empirical studies show that the feedback directed technique significantly improves upon existing techniques and helps to identify serious problems in fielded GUIs. Another set of studies conducted on in-house software applications show that the test suites generated by the new technique outperform their coverage equivalent counterparts in terms of fault detection. Although the focus of this work is on the GUI domain, the techniques developed are general and are applicable to the broader class of EDS. In fact, this work has already had an impact on research and practice of testing other EDS. In particular, the work has been extended by other researchers to test web applications

Model-based testing of automotive HMIs with consideration for product variability

The human-machine interfaces (HMIs) of today’s premium automotive infotainment systems are complex embedded systems which have special characteristics in comparison to GUIs of standard PC applications, in particular regarding their variability. The variability of infotainment system HMIs results from different car models, product series, markets, equipment configuration possibilities, system types and languages and necessitates enormous testing efforts. The model-based testing approach is a promising solution for reducing testing efforts and increasing test coverage. However, while model-based testing has been widely used for function tests of subsystems in practice, HMI tests have remained manual or only semi-automated and are very time-consuming and work-intensive. Also, it is very difficult to achieve systematic or high test coverage via manual tests. A large amount of research work has addressed GUI testing in recent years. In addition, variability is becoming an ever more popular topic in the domain of software product line development. However, a model-based testing approach for complex HMIs which also considers variability is still lacking. This thesis presents a model-based testing approach for infotainment system HMIs with the particular aim of resolving the variability problem. Furthermore, the thesis provides a foundation for future standards of HMI testing in practice. The proposed approach is based on a model-based HMI testing framework which includes two essential components: a test-oriented HMI specification and a test generation component. The test-oriented HMI specification has a layered structure and is suited to specifying data which is required for testing different features of the HMI. Both the dynamic behavior and the representation of the HMI are the testing focuses of this thesis. The test generation component automatically generates tests from the test-oriented HMI specification. Furthermore, the framework can be extended in order to automatically execute the generated tests. Generated tests must first be initialized, which means that they are enhanced with concrete user input data. Afterwards, initialized tests can be automatically executed with the help of a test execution tool which must be extended into the testing framework. In this thesis, it is proposed to specify and test different HMI-variants which have a large set of commonalities based on the software product line approach. This means the test-oriented HMI specification is extended in order to describe the commonalities and variabilities between HMI variants of an HMI product line. In particular, strategies are developed in order to generate tests for different HMI products. One special feature is that redundancies are avoided both for the test generation and the execution processes. This is especially important for the industrial practice due to limited test resources. Modeling and testing variability of automotive HMIs make up the main research contributions of this thesis. We hope that the results presented in this thesis will offer GUI testing research a solution for model-based testing of multi-variant HMIs and provide the automotive industry with a foundation for future HMI testing standards