Smart TV application (app) is a new technological software app that can deal with smart TV devices to add more functionality and features. Despite its importance nowadays, far too little attention has been paid to present a systematic approach to test this kind of app so far. In this paper, we present a systematic model-based testing approach for smart TV app. We used our new notion of model separation to use sub-models based on the user preference instead of the exhaustive testing to generate the test cases. Based on the constructed model, we generated a set of test cases to assess the selected paths to the chosen destination in the app. We also defined new mutation operators for smart TV app to assess our testing approach. The evaluation results showed that our approach can generate more comprehensive models of smart TV apps with less time as compared to manual exploratory testing. The results also showed that our approach can generate effective test cases in term of fault detection.
Context: Smart TVs have become one of the most popular television types. Many app developers and service providers have designed TV versions for their smartphone applications. Despite the extensive studies on mobile app analysis, its TV equivalents receive far too little attention. The relationship between phone and TV has not been the subject of research works. Objective: In this paper, we aim to characterize the relationship between smartphone and smart TV apps. To fill this gap, we conduct a comparative study on smartphone and smart TV apps in this work, which is the starting and fundamenta…
As the popularity of Smart Televisions (TVs) and interactive Smart TV applications (apps) has recently grown, the usability of these apps has become an important quality characteristic. Previous studies examined Smart TV apps from a usability perspective. However, these methods are mainly manual, and the potential of automated model-based testing methods for usability testing purposes has not yet been fully explored. In this paper, we propose an approach to test the usability of Smart TV apps based on the automated generation of a Smart TV user interaction model from an existing app by a speci…
Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the r…
A large percentage of buildings, domestic or special-purpose, is expected to become increasingly "smarter" in the future, due to the immense benefits in terms of energy saving, safety, flexibility, and comfort, that relevant new technologies offer. However, concerning the hardware, software, or platform levels, no clearly dominant standard frameworks currently exist. Here, we will present a prototype platform for supporting multiple concurrent applications for smart buildings, which is utilizing an advanced sensor network as well as a distributed micro services architecture, centrally featurin…
Android apps are GUI-based event-driven software and have become ubiquitous in recent years. Obviously, functional correctness is critical for an app's success. However, in addition to crash bugs, non-crashing functional bugs (in short as "non-crashing bugs" in this work) like inadvertent function failures, silent user data lost and incorrect display information are prevalent, even in popular, well-tested apps. These non-crashing functional bugs are usually caused by program logic errors and manifest themselves on the graphic user interfaces (GUIs). In practice, such bugs pose significant chal…
Mobile apps are now ubiquitous. Before developing a new app, the development team usually endeavors painstaking efforts to review many existing apps with similar purposes. The review process is crucial in the sense that it reduces market risks and provides inspiration for app development. However, manual exploration of hundreds of existing apps by different roles (e.g., product manager, UI/UX designer, developer) in a development team can be ineffective. For example, it is difficult to completely explore all the functionalities of the app in a short period of time. Inspired by the conception o…
The mobile application (app) has become the main entrance to access the Internet on handheld devices. Unlike the Web where each webpage has a global URL to reach directly, a specific "content page" of an app can be opened only by exploring the app with several operations from the landing page. The interoperability between apps is quite fixed and thus limits the value-added "linked data" between apps. Recently, deep link has been proposed to enable targeting and opening a specific page of an app externally with an accessible uniform resource identifier (URI). However, implementing deep link for…
The advancement of artificial intelligence (AI) and the significant growth in the use of food consumption tracking and recommendation-related apps in the app stores have created a need for an evaluation system, as minimal information is available about the evidence-based quality and technological advancement of these apps. Electronic searches were conducted across three major app stores and the selected apps were evaluated by three independent raters. A total of 473 apps were found and 80 of them were selected for review based on inclusion and exclusion criteria. An app rating tool is devised …
When smartphones, applications (a.k.a, apps), and app stores have been widely adopted by the billions, an interesting debate emerges: whether and to what extent do device models influence the behaviors of their users? The answer to this question is critical to almost every stakeholder in the smartphone app ecosystem, including app store operators, developers, end-users, and network providers. To approach this question, we collect a longitudinal data set of app usage through a leading Android app store in China, called Wandoujia. The data set covers the detailed behavioral profiles of 0.7 milli…
Human values such as integrity, privacy, curiosity, security, and honesty are guiding principles for what people consider important in life. Such human values may be violated by mobile software applications (apps), and the negative effects of such human value violations can be seen in various ways in society. In this work, we focus on the human value of honesty. We present a model to support the automatic identification of violations of the value of honesty from app reviews from an end-user perspective. Beyond the automatic detection of honesty violations by apps, we also aim to better underst…
Internet of Things (IoT) devices are becoming increasingly important. These devices are often resource-limited, hindering rigorous enforcement of security policies. Assessing the vulnerability of IoT devices is an important problem, but analyzing their firmware is difficult for a variety of reasons, including requiring the purchase of devices. This paper finds that analyzing companion apps to these devices for clues to security vulnerabilities can be an effective strategy. Compared to device hardware and firmware, these apps are easy to download and analyze. A key finding of this study is that…
Human values such as honesty, social responsibility, fairness, privacy, and the like are things considered important by individuals and society. Software systems, including mobile software applications (apps), may ignore or violate such values, leading to negative effects in various ways for individuals and society. While some works have investigated different aspects of human values in software engineering, this mixed-methods study focuses on honesty as a critical human value. In particular, we studied (i) how to detect honesty violations in mobile apps, (ii) the types of honesty violations i…
Bug reports are vital for software maintenance that allow users to inform developers of the problems encountered while using software. However, it is difficult for non-technical users to write clear descriptions about the bug occurrence. Therefore, more and more users begin to record the screen for reporting bugs as it is easy to be created and contains detailed procedures triggering the bug. But it is still tedious and time-consuming for developers to reproduce the bug due to the length and unclear actions within the recording. To overcome these issues, we propose GIFdroid, a light-weight app…
The inception of a mobile app often takes form of a mock-up of the Graphical User Interface (GUI), represented as a static image delineating the proper layout and style of GUI widgets that satisfy requirements. Following this initial mock-up, the design artifacts are then handed off to developers whose goal is to accurately implement these GUIs and the desired functionality in code. Given the sizable abstraction gap between mock-ups and code, developers often introduce mistakes related to the GUI that can negatively impact an app's success in highly competitive marketplaces. Moreover, such mis…
App store mining has proven to be a promising technique for requirements elicitation as companies can gain valuable knowledge to maintain and evolve existing apps. However, despite first advancements in using mining techniques for requirements elicitation, little is yet known how to distill requirements for new apps based on existing (similar) solutions and how exactly practitioners would benefit from such a technique. In the proposed work, we focus on exploring information (e.g. app store data) provided by the crowd about existing solutions to identify key features of applications in a partic…
With smartphone technologies enhanced way of interacting with the world around us, it has also been paving the way for easier access to our private and personal information. This has been amplified by the existence of numerous embedded sensors utilized by millions of apps to users. While mobile apps have positively transformed many aspects of our lives with new functionalities, many of these applications are taking advantage of vast amounts of data, privacy apps, a form of Privacy Enhancing Technology can be an effective privacy management tool for smartphones. To protect against vulnerabiliti…
On-device deep learning is rapidly gaining popularity in mobile applications. Compared to offloading deep learning from smartphones to the cloud, on-device deep learning enables offline model inference while preserving user privacy. However, such mechanisms inevitably store models on users' smartphones and may invite adversarial attacks as they are accessible to attackers. Due to the characteristic of the on-device model, most existing adversarial attacks cannot be directly applied for on-device models. In this paper, we introduce a grey-box adversarial attack framework to hack on-device model…
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 a…
Smart cities are a growing trend in many cities in Argentina. In particular, the so-called intermediate cities present a context and requirements different from those of large cities with respect to smart cities. One aspect of relevance is to encourage the development of applications (generally for mobile devices) that enable citizens to take advantage of data and services normally associated with the city, for example, in the urban mobility domain. In this work, a platform is proposed for intermediate cities that provide "high level" services and that allow the construction of software applic…
This paper presents a fully automated static analysis approach and a tool, Taint-Things, for the identification of tainted flows in SmartThings IoT apps. Taint-Things accurately identifies all tainted flows reported by one of the state-of-the-art tools with at least 4 times improved performance. Our approach reports potential vulnerable tainted flows in a form of a concise security slice, where the relevant parts of the code are given with the lines affecting the sensitive information, which could provide security auditors with an effective and precise tool to pinpoint security issues in Smart…
The functionality of many mobile applications is dependent on various contextual, external factors. Depending on unforeseen scenarios, mobile apps can even malfunction or crash. In this paper, we have introduced MobiCoMonkey - automated tool that allows a developer to test app against custom or auto generated contextual scenarios and help detect possible bugs through the emulator. Moreover, it reports the connection between the bugs and contextual factors so that the bugs can later be reproduced. It utilizes the tools offered by Android SDK and logcat to inject events and capture traces of the…
Spotting Setting-Related UI Display Bugs in Android Apps
School of Informatics (National Characteristic Demonstration Software School), Xiamen University（厦门大学信息学院（国家示范性软件学院））；Fujian Engineering Research Center of High-Performance Intelligent Computing Systems（福建省高性能智能计算系统工程研究中心）
Data driven research on Android has gained a great momentum these years. The abundance of data facilitates knowledge learning, however, also increases the difficulty of data preprocessing. Therefore, it is non-trivial to prepare a demanding and accurate set of data for research. In this work, we put forward AndroVault, a framework for the Android research composing of data collection, knowledge representation and knowledge extraction. It has started with a long-running web crawler for data collection (both apps and description) since 2013, which guarantees the timeliness of data; With static a…
Because Mobile apps are extremely popular and often mission critical nowadays, companies invest a great deal of resources in testing the apps they provide to their customers. Testing is particularly important for Android apps, which must run on a multitude of devices and operating system versions. Unfortunately, as we confirmed in many interviews with quality assurance professionals, app testing is today a very human intensive, and therefore tedious and error prone, activity. To address this problem, and better support testing of Android apps, we propose a new technique that allows testers to …
One of the key tasks related to ensuring mobile app quality is the reporting, management, and resolution of bug reports. As such, researchers have committed considerable resources toward automating various tasks of the bug management process for mobile apps, such as reproduction and triaging. However, the success of these automated approaches is largely dictated by the characteristics and properties of the bug reports they operate upon. As such, understanding mobile app bug reports is imperative to drive the continued advancement of report management techniques. While prior studies have examin…
Failure to consider the characteristics, limitations, and abilities of diverse end-users during mobile apps development may lead to problems for end-users such as accessibility and usability issues. We refer to this class of problems as human-centric issues. Despite their importance, there is a limited understanding of the types of human-centric issues that are encountered by end-users and taken into account by the developers of mobile apps. In this paper, we examine what human-centric issues end-users report through Google App Store reviews, which human-centric issues are a topic of discussio…
Automated input generators are widely used for large-scale dynamic analysis of mobile apps. Such input generators must constantly choose which UI element to interact with and how to interact with it, in order to achieve high coverage with a limited time budget. Currently, most input generators adopt pseudo-random or brute-force searching strategies, which may take very long to find the correct combination of inputs that can drive the app into new and important states. In this paper, we propose Humanoid, a deep learning-based approach to GUI test input generation by learning from human interact…
Advertisement drives the economy of the mobile app ecosystem. As a key component in the mobile ad business model, mobile ad content has been overlooked by the research community, which poses a number of threats, e.g., propagating malware and undesirable contents. To understand the practice of these devious ad behaviors, we perform a large-scale study on the app contents harvested through automated app testing. In this work, we first provide a comprehensive categorization of devious ad contents, including five kinds of behaviors belonging to two categories: \emph{ad loading content} and \emph{a…
Over the last few years, there has been substantial research on automated analysis, testing, and debugging of Ethereum smart contracts. However, it is not trivial to compare and reproduce that research. To address this, we present an empirical evaluation of 9 state-of-the-art automated analysis tools using two new datasets: i) a dataset of 69 annotated vulnerable smart contracts that can be used to evaluate the precision of analysis tools; and ii) a dataset with all the smart contracts in the Ethereum Blockchain that have Solidity source code available on Etherscan (a total of 47,518 contracts…
Android apps must work correctly even if their execution is interrupted by external events. For instance, an app must work properly even if a phone call is received, or after its layout is redrawn because the smartphone has been rotated. Since these events may require destroying, when the execution is interrupted, and recreating, when the execution is resumed, the foreground activity of the app, the only way to prevent the loss of state information is saving and restoring it. This behavior must be explicitly implemented by app developers, who often miss to implement it properly, releasing apps…
As smartphones become increasingly more powerful, a new generation of highly interactive user-centric mobile apps emerge to make user's life simpler and more productive. Mobile phones applications have to sustain limited resource availability on mobile devices such as battery life, network connectivity while also providing better responsiveness, lightweight interactions within the application. Developers end up spending a considerable amount of time dealing with the architecture constraints imposed by the wide variety of platforms, tools, and devices offered by the mobile ecosystem, thereby di…
Mobile apps are indispensable for people's daily life. Complementing with automated GUI testing, manual testing is the last line of defence for app quality. However, the repeated actions and easily missing of functionalities make manual testing time-consuming and inefficient. Inspired by the game candy crush with flashy candies as hint moves for players, we propose an approach named NaviDroid for navigating testers via highlighted next operations for more effective and efficient testing. Within NaviDroid, we construct an enriched state transition graph with the triggering actions as the edges …
With the popularity of Android apps, different techniques have been proposed to enhance app protection. As an effective approach to prevent reverse engineering, obfuscation can be used to serve both benign and malicious purposes. In recent years, more and more sensitive logic or data have been implemented as obfuscated native code because of the limitations of Java bytecode. As a result, native code obfuscation becomes a great obstacle for security analysis to understand the complicated logic. In this paper, we propose DiANa, an automated system to facilitate the deobfuscation of native binary…
Android OS supports multiple communication methods between apps. This opens the possibility to carry out threats in a collaborative fashion, c.f. the Soundcomber example from 2011. In this paper we provide a concise definition of collusion and report on a number of automated detection approaches, developed in co-operation with Intel Security.
Android has been the most popular smartphone system with multiple platform versions active in the market. To manage the application's compatibility with one or more platform versions, Android allows apps to declare the supported platform SDK versions in their manifest files. In this paper, we conduct a systematic study of this modern software mechanism. Our objective is to measure the current practice of declared SDK versions (which we term as DSDK versions afterwards) in real apps, and the (in)consistency between DSDK versions and their host apps' API calls. To successfully analyze a modern d…
Recent studies showed that the dialogs between app developers and app users on app stores are important to increase user satisfaction and app's overall ratings. However, the large volume of reviews and the limitation of resources discourage app developers from engaging with customers through this channel. One solution to this problem is to develop an Automated Responding System for developers to respond to app reviews in a manner that is most similar to a human response. Toward designing such system, we have conducted an empirical study of the characteristics of mobile apps' reviews and their …
Today, there are millions of third-party Android applications. Some of these applications are buggy or even malicious. To identify such applications, novel frameworks for automated black-box testing and dynamic analysis are being developed by the Android community, including Google. Code coverage is one of the most common metrics for evaluating effectiveness of these frameworks. Furthermore, code coverage is used as a fitness function for guiding evolutionary and fuzzy testing techniques. However, there are no reliable tools for measuring fine-grained code coverage in black-box Android app tes…
