Similarity-based Web Element Localization for Robust Test Automation

Non-robust (fragile) test execution is a commonly reported challenge in GUI-based test automation, despite much research and several proposed solutions. A test script needs to be resilient to (minor) changes in the tested application but, at the same time, fail when detecting potential issues that require investigation. Test script fragility is a multi-faceted problem. However, one crucial challenge is how to reliably identify and locate the correct target web elements when the website evolves between releases or otherwise fail and report an issue. This article proposes and evaluates a novel approach called similarity-based web element localization (Similo), which leverages information from multiple web element locator parameters to identify a target element using a weighted similarity score. This experimental study compares Similo to a baseline approach for web element localization. To get an extensive empirical basis, we target 48 of the most popular websites on the Internet in our evaluation. Robustness is considered by counting the number of web elements found in a recent website version compared to how many of these existed in an older version. Results of the experiment show that Similo outperforms the baseline; it failed to locate the correct target web element in 91 out of 801 considered cases (i.e., 11%) compared to 214 failed cases (i.e., 27%) for the baseline approach. The time efficiency of Similo was also considered, where the average time to locate a web element was determined to be 4 milliseconds. However, since the cost of web interactions (e.g., a click) is typically on the order of hundreds of milliseconds, the additional computational demands of Similo can be considered negligible. This study presents evidence that quantifying the similarity between multiple attributes of web elements when trying to locate them, as in our proposed Similo approach, is beneficial. With acceptable efficiency, Similo gives significantly higher effectiveness (i.e., robustness) than the baseline web element localization approach

Evolution and Fragility of Mobile Automated Test Suites

L'abstract è presente nell'allegato / the abstract is in the attachmen

Towards a hybrid testing process unifying exploratory testing and scripted testing

CONTEXT Given the current state of the art in research, practitioners are faced with the challenge of choosing scripted testing (ST) or exploratory testing (ET). OBJECTIVE This study aims at systematically incorporating strengths of ET and ST in a hybrid testing process to overcome the weaknesses of each. METHOD We utilized systematic review and practitioner interviews to identify strengths and weaknesses of ET and ST. Strengths of ET were mapped to weaknesses of ST and vice versa. Noblit and Hare's lines-ofargument method was used for data analysis. The results of the mapping were used as input to codesign a hybrid process with experienced practitioners. RESULTS We found a clear need to create a hybrid process as follows: (i) both ST and ET provide strengths and weaknesses, and these depend on some particular conditions, which prevents preference of one approach to another; and (ii) the mapping showed that it is possible to address the weaknesses in one process by the strengths of the other in a hybrid form. With the input from literature and industry experts, a flexible and iterative hybrid process was designed. CONCLUSIONS Practitioners can clearly benefit from using a hybrid process given the mapping of advantages and disadvantage

Dynamic Honeypot Configuration for Programmable Logic Controller Emulation

Attacks on industrial control systems and critical infrastructure are on the rise. Important systems and devices like programmable logic controllers are at risk due to outdated technology and ad hoc security measures. To mitigate the threat, honeypots are deployed to gather data on malicious intrusions and exploitation techniques. While virtual honeypots mitigate the unreasonable cost of hardware-replicated honeypots, these systems often suffer from a lack of authenticity due to proprietary hardware and network protocols. In addition, virtual honeynets utilizing a proxy to a live device suffer from performance bottlenecks and limited scalability. This research develops an enhanced, application layer emulator capable of alleviating honeynet scalability and honeypot inauthenticity limitations. The proposed emulator combines protocol-agnostic replay with dynamic updating via a proxy. The result is a software tool which can be readily integrated into existing honeypot frameworks for improved performance. The proposed emulator is evaluated on traffic reduction on the back-end proxy device, application layer task accuracy, and byte-level traffic accuracy. Experiments show the emulator is able to successfully reduce the load on the proxy device by up to 98% for some protocols. The emulator also provides equal or greater accuracy over a design which does not use a proxy. At the byte level, traffic variation is statistically equivalent while task success rates increase by 14% to 90% depending on the protocol. Finally, of the proposed proxy synchronization algorithms, templock and its minimal variant are found to provide the best overall performance

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

Test Advising Framework

Test cases are represented in various formats depending on the process, the technique or the tool used to generate the tests. While different test case representations are necessary, this diversity challenges us in comparing test cases and leveraging strengths among them - a common test representation will help. In this thesis, we define a new Test Case Language (TCL) that can be used to represent test cases that vary in structure and are generated by multiple test generation frameworks. We also present a methodology for transforming test cases of varying representations into a common format where they can be matched and analyzed. With the common representation in our test case description language, we define five advice functions to leverage the testing strength from one type of tests to improve the effectiveness of other type(s) of tests. These advice functions analyze test input values, method call sequences, or test oracles of one source test suite to derive advice, and utilize the advice to amplify the effectiveness of an original test suite. Our assessment shows that the amplified test suite derived from the advice functions has improved values in terms of code coverage and mutant kill score compared to the original test suite before the advice functions applied

Supporting Evolution and Maintenance of android Apps

Mobile developers and testers face a number of emerging challenges. These include rapid platform evolution and API instability; issues in bug reporting and reproduction involving complex multitouch gestures; platform fragmentation; the impact of reviews and ratings on the success of their apps; management of crowd-sourced requirements; continuous pressure from the market for frequent releases; lack of effective and usable testing tools; and limited computational resources for handheld devices. Traditional and contemporary methods in software evolution and maintenance were not designed for these types of challenges; therefore, a set of studies and a new toolbox of techniques for mobile development are required to analyze current challenges and propose new solutions. This dissertation presents a set of empirical studies, as well as solutions for some of the key challenges when evolving and maintaining android apps. In particular, we analyzed key challenges experienced by practitioners and open issues in the mobile development community such as (i) android API instability, (ii) performance optimizations, (iii) automatic GUI testing, and (iv) energy consumption. When carrying out the studies, we relied on qualitative and quantitative analyses to understand the phenomena on a large scale by considering evidence extracted from software repositories and the opinions of open-source mobile developers. From the empirical studies, we identified that dynamic analysis is a relevant method for several evolution and maintenance tasks, in particular, because of the need of practitioners to execute/validate the apps on a diverse set of platforms (i.e., device and OS) and under pressure for continuous delivery. Therefore, we designed and implemented an extensible infrastructure that enables large-scale automatic execution of android apps to support different evolution and maintenance tasks (e.g., testing and energy optimization). In addition to the infrastructure we present a taxonomy of issues, single solutions to the issues, and guidelines to enable large execution of android apps. Finally, we devised novel approaches aimed at supporting testing and energy optimization of mobile apps (two key challenges in evolution and maintenance of android apps). First, we propose a novel hybrid approach for automatic GUI-based testing of apps that is able to generate (un)natural test sequences by mining real applications usages and learning statistical models that represent the GUI interactions. In addition, we propose a multi-objective approach for optimizing the energy consumption of GUIs in android apps that is able to generate visually appealing color compositions, while reducing the energy consumption and keeping a design concept close to the original

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

Experimental user interface design toolkit for interaction research (IDTR).

The research reported and discussed in this thesis represents a novel approach to User Interface evaluation and optimisation through cognitive modelling. This is achieved through the development and testing of a toolkit or platform titled Toolkit for Optimisation of Interface System Evolution (TOISE). The research is conducted in two main phases. In phase 1, the Adaptive Control of Thought Rational (ACT-R) cognitive architecture is used to design Simulated Users (SU) models. This allows models of user interaction to be tested on a specific User Interface (UI). In phase 2, an evolutionary algorithm is added and used to evolve and test an optimised solution to User Interface layout based on the original interface design. The thesis presents a technical background, followed by an overview of some applications in their respective fields. The core concepts behind TOISE are introduced through a discussion of the Adaptive Control of Thought “ Rational (ACT-R) architecture with a focus on the ACT-R models that are used to simulate users. The notion of adding a Genetic Algorithm optimiser is introduced and discussed in terms of the feasibility of using simulated users as the basis for automated evaluation to optimise usability. The design and implementation of TOISE is presented and discussed followed by a series of experiments that evaluate the TOISE system. While the research had to address and solve a large number of technical problems the resulting system does demonstrate potential as a platform for automated evaluation and optimisation of user interface layouts. The limitations of the system and the approach are discussed and further work is presented. It is concluded that the research is novel and shows considerable promise in terms of feasibility and potential for optimising layout for enhanced usability