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

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

Semantic mutation testing

This is the Pre-print version of the Article. The official published version can be obtained from the link below - Copyright @ 2011 ElsevierMutation testing is a powerful and flexible test technique. Traditional mutation testing makes a small change to the syntax of a description (usually a program) in order to create a mutant. A test suite is considered to be good if it distinguishes between the original description and all of the (functionally non-equivalent) mutants. These mutants can be seen as representing potential small slips and thus mutation testing aims to produce a test suite that is good at finding such slips. It has also been argued that a test suite that finds such small changes is likely to find larger changes. This paper describes a new approach to mutation testing, called semantic mutation testing. Rather than mutate the description, semantic mutation testing mutates the semantics of the language in which the description is written. The mutations of the semantics of the language represent possible misunderstandings of the description language and thus capture a different class of faults. Since the likely misunderstandings are highly context dependent, this context should be used to determine which semantic mutants should be produced. The approach is illustrated through examples with statecharts and C code. The paper also describes a semantic mutation testing tool for C and the results of experiments that investigated the nature of some semantic mutation operators for C

A Context-Sensitive Coverage Criterion for Test Suite Reduction

Modern software is increasingly developed using multi-language implementations, large supporting libraries and frameworks, callbacks, virtual function calls, reflection, multithreading, and object- and aspect-oriented programming. The predominant example of such software is the graphical user interface (GUI), which is used as a front-end to most of today's software applications. The characteristics of GUIs and other modern software present new challenges to software testing. Because recently developed techniques for automated test case generation can generate more tests than are practical to regularly execute, one important challenge is test suite reduction. Test suite reduction seeks to decrease the size of a test suite without overly compromising its original fault detection ability. This research advances the state-of-the-art in test suite reduction by empirically studying a coverage criterion which considers the context in which program concepts are covered. Conventional approaches to test suite reduction were developed and evaluated on batch-style applications and, due to the aforementioned considerations, are not always easily applicable to modern software. Furthermore, many existing techniques fail to consider the context in which code executes inside an event-driven paradigm, where programs wait for and interactively respond to user- and system-generated events. Consequently, they yield reduced test suites with severely impaired fault detection ability. The novel feature of this research is a test suite reduction technique based on the call stack coverage criterion which addresses many of the challenges associated with coverage-based test suite reduction in modern applications. Results show that reducing test suites while maintaining call stack coverage yields good tradeoffs between size reduction and fault detection effectiveness compared to traditional techniques. The output of this research includes models, metrics, algorithms, and techniques based upon this approach

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

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