Automated Test Input Generation for Android: Are We There Yet?

Mobile applications, often simply called "apps", are increasingly widespread, and we use them daily to perform a number of activities. Like all software, apps must be adequately tested to gain confidence that they behave correctly. Therefore, in recent years, researchers and practitioners alike have begun to investigate ways to automate apps testing. In particular, because of Android's open source nature and its large share of the market, a great deal of research has been performed on input generation techniques for apps that run on the Android operating systems. At this point in time, there are in fact a number of such techniques in the literature, which differ in the way they generate inputs, the strategy they use to explore the behavior of the app under test, and the specific heuristics they use. To better understand the strengths and weaknesses of these existing approaches, and get general insight on ways they could be made more effective, in this paper we perform a thorough comparison of the main existing test input generation tools for Android. In our comparison, we evaluate the effectiveness of these tools, and their corresponding techniques, according to four metrics: code coverage, ability to detect faults, ability to work on multiple platforms, and ease of use. Our results provide a clear picture of the state of the art in input generation for Android apps and identify future research directions that, if suitably investigated, could lead to more effective and efficient testing tools for Android

A large-scale empirical study on mobile performance: energy, run-time and memory

Software performance concerns have been attracting research interest at an increasing rate, especially regarding energy performance in non-wired computing devices. In the context of mobile devices, several research works have been devoted to assessing the performance of software and its underlying code. One important contribution of such research efforts is sets of programming guidelines aiming at identifying efficient and inefficient programming practices, and consequently to steer software developers to write performance-friendly code. Despite recent efforts in this direction, it is still almost unfeasible to obtain universal and up-to-date knowledge regarding software and respective source code performance. Namely regarding energy performance, where there has been growing interest in optimizing software energy consumption due to the power restrictions of such devices. There are still many difficulties reported by the community in measuring performance, namely in large-scale validation and replication. The Android ecosystem is a particular example, where the great fragmentation of the platform, the constant evolution of the hardware, the software platform, the development libraries themselves, and the fact that most of the platform tools are integrated into the IDE’s GUI, makes it extremely difficult to perform performance studies based on large sets of data/applications. In this paper, we analyze the execution of a diversified corpus of applications of significant magnitude. We analyze the source-code performance of 1322 versions of 215 different Android applications, dynamically executed with over than 27900 tested scenarios, using state-of-the-art black-box testing frameworks with different combinations of GUI inputs. Our empirical analysis allowed to observe that semantic program changes such as adding functionality and repairing bugfixes are the changes more associated with relevant impact on energy performance. Furthermore, we also demonstrate that several coding practices previously identified as energy-EC - European Commission(19135); National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia, within project UIDP/50014/2020, by COST Action 19135: “CERICIRAS - Connecting Education and Research Communities for an Innovative Resource Aware Society”, and by Erasmus+ project No. 2020-1-PT01-KA203-078646: “SusTrainable - Promoting Sustainability as a Fundamental Driver in Software Development Training and Education”. The first author is also financed by FCT grant SFRH/BD/146624/201

Systemic Efficiencies in Competition Law: Evidence from the ICT Industry

This article introduces the concept of systemic efficiencies, traces its theoretical underpinnings in economics, management and technology, and applies it to recent high profile cases. Systemic efficiencies occur in large complex systems through the interaction of multiple distributed components, a process which is commonly coordinated by an entity that can exercise pervasive control over the components and their interactions. This type of extensive control can manifest itself as potentially anticompetitive practices, like tying, refusal to deal and full line forcing, causing the reaction of competition authorities. However, at the same time, systemic efficiencies can have significant benefits that cannot be generated by smaller scale, simpler, more isolated efficiencies, and are therefore of great interest to society, and of high redeeming value as antitrust defence to the introducing entities. To demonstrate how systemic efficiencies and their benefits materialize in practice this article also discusses two series of cases: the recent IBM mainframes cases in the US and the US, and the ongoing Google Android cases in the US and the EU. Both cases belong in the ICT industry, which is frequently said to consist of paradigmatic examples of large complex systems that can give rise to systemic efficiencies

Thesis title: Crowdsourced Testing Approach For Mobile Compatibility Testing

The frequent release of mobile devices and operating system versions bring several compatibility issues to mobile applications. This thesis addresses fragmentation-induced compatibility issues. The thesis comprises three main phases. The first of these involves an in-depth review of relevant literature that identifies the main challenges of existing compatibility testing approaches. The second phase reflects on the conduction of an in-depth exploratory study on Android/iOS developers in academia and industry to gain further insight into their actual needs in testing environments whilst gauging their willingness to work with public testers with varied experience. The third phase relates to implementing a new manual crowdtesting approach that supports large-scale distribution of tests and execution by public testers and real users on a larger number of devices in a short time. The approach is designed based on a direct crowdtesting workflow to bridge the communication gap between developers and testers. The approach supports performing the three dimensions of compatibility testing. This approach helps explore different behaviours of the app and the users of the app to identify all compatibility issues. Two empirical evaluation studies were conducted on iOS/Android developers and testers to gauge developers' and testers' perspectives regarding the benefits, satisfaction, and effectiveness of the proposed approach. Our findings show that the approach is effective and improves on current state-of-the-art approaches. The findings also show that the approach met the several unmet needs of different groups of developers and testers. The evaluation proved that the different groups of developers and testers were satisfied with the approach. Importantly, the level of satisfaction was especially high in small and medium-sized enterprises that have limited access to traditional testing infrastructures, which are instead present in large enterprises. This is the first research that provides insights for future research into the actual needs of each group of developers and testers