Automated Testing of Android Apps: a Systematic Literature Review

Automated Testing of Android Apps: a Systematic Literature Review

1 Automated Testing of Android Apps: A Systematic Literature Review Pingfan Kong, Li Liξ, Jun Gao, Kui Liu, Tegawende´ F. Bissyande,´ Jacques Klein F Abstract—Automated testing of Android apps is essential for app users, app developers and market maintainer communities alike. Given the (1) Install App (2) Static widespread adoption of Android and the specificities of its develop- Analysis (3) Send Test Cases ment model, the literature has proposed various testing approaches for (4) Observe Execution ensuring that not only functional requirements but also non-functional Behaviour requirements are satisfied. In this paper, we aim at providing a clear (5) Clean Environment overview of the state-of-the-art works around the topic of Android app Testing AndroidTesting Approaches Environment testing, in an attempt to highlight the main trends, pinpoint the main Approaches Device methodologies applied and enumerate the challenges faced by the An- droid testing approaches as well as the directions where the community Fig. 1: Process of testing Android apps. effort is still needed. To this end, we conduct a Systematic Literature Review (SLR) during which we eventually identified 103 relevant re- search papers published in leading conferences and journals until 2016. by Kochhar [3], error-prone apps can significantly impact Our thorough examination of the relevant literature has led to several user experience and lead to a downgrade of their ratings, findings and highlighted the challenges that Android testing researchers eventually harming the reputation of app developers and should strive to address in the future. After that, we further propose a their organizations [5]. It is thus becoming more and more few concrete research directions where testing approaches are needed to solve recurrent issues in app updates, continuous increases of app important to ensure that Android apps are sufficiently tested sizes, as well as the Android ecosystem fragmentation. before they are released on the market. However, instead of manual testing, which is often laborious, time-consuming and error-prone, the ever-growing complexity and the enor- 1 INTRODUCTION mous number of Android apps call for scalable, robust and trustworthy automated testing solutions. Android smart devices have become pervasive after gaining Android app testing aims at testing the functionality, tremendous popularity in recent years. As of July 2017, usability and compatibility of apps running on Android Google Play, the official app store, is distributing over devices [6], [7]. Fig. 1 illustrates a typical working process. 3 million Android applications (i.e., apps), covering over At Step (1), target app is installed on an Android device. 30 categories ranging from entertainment and personali- Then in Step (2), the app is analysed to generate test cases. sation apps to education and financial apps. Such popu- We remind the readers that this step (in dashed line) is larity among developer communities can be attributed to optional and some testing techniques such as automated the accessible development environment based on familiar random testing do not need to obtain pre-knowledge for Java programming language as well as the availability of generating test cases. Subsequently, in Step (3), these test libraries implementing diverse functionalities [1]. The app cases are sent to the Android device to exercise the app. distribution ecosystem around the official store and other In Step (4), execution behaviour is observed and collected alternative stores such as Anzhi and AppChina is further from all sorts of perspectives. Finally, in Step (5), the app attractive for users to find apps and organisations to market is uninstalled and relevant data is wiped. We would like their apps [2]. to remind the readers that installation of the target app is Unfortunately, the distribution ecosystem of Android sometimes not a necessity, e.g., frameworks like Robolectric is porous to poorly-tested apps [3]–[5]. Yet, as reported allow tests directly run in JVM. In fact, Fig. 1 can be borrowed to describe the workflow of testing almost any ξ • The corresponding author. software besides Android apps. Android app testing, on the • P. Kong, J. Gao, K. Liu, T. Bissyand´e, and J. Klein are with the In- terdisciplinary Centre for Security, Reliability and Trust, University of contrary, falls in a unique context and often fails to use Luxembourg, Luxembourg. general testing techniques [8]–[13]. There are several dif- • L. Li is with the Faculty of Information Technology, Monash University, ferences with traditional (e.g., Java) application testing that Australia. E-mail: [email protected] motivate research on Android app testing. We enumerate and consider for our review a few common challenges: Manuscript received XXX; revised XXX.This work was supported by the Fonds National de la Recherche (FNR), Luxembourg, under projects CHAR- First, although apps are developed in Java, traditional ACTERIZE C17/IS/11693861 and Recommend C15/IS/10449467. Java-based testing tools are not immediately usable on An- 2 droid apps since most control-flow interactions in Android Research Question Exclusion Criteria are governed by specific event-based mechanisms such as Identification Application the Inter-Component Communication (ICC [14]). To address this first challenge, several new testing tools have been Keywords Primary Identification Publications specifically designed for taking Android specificities into account. For example, RERAN [15] was proposed for testing Repository CCF-Ranked Data Extraction Android apps through a timing- and touch-sensitive record- Search Venues Search and-replay mechanism, in an attempt to capture, represent and replay complicated non-discrete gestures such as circu- lar bird swipe with increasing slingshot tension in Angry Birds. Results Merging Cross Checking Second, Android fragmentation, in terms of the diversity of available OS versions and target devices (e.g., screen size Harvested SLR Report varieties), is becoming acuter as now testing strategies have Publications to take into account different execution contexts [16], [17]. Third, the Android ecosystem attracts a massive number Fig. 2: Process of the SLR. of apps requiring scalable approaches to testing. Further- more, these apps do not generally come with open source code, which may constrain the testing scenarios. and categorising all related research works. Finally, it is challenging to generate a perfect coverage of • Finally, we investigate the current state of the art, test cases, in order to find faults in Android apps. Traditional enumerate the salient limitations and pinpoint a few test case generation approaches based on symbolic execution directions for furthering the research in Android test- and tools such as Symbolic Pathfinder (SPF) are challenged by ing. the fact that Android apps are available in Dalvik bytecode The rest of the paper is organized as follows: Section 2 that differs from Java bytecode. In other words, traditional depicts the methodology of this systematic literature review, Java-based symbolic execution approaches cannot be di- including a general overview and detailed reviewing pro- rectly applied to tackle Android apps. Furthermore, the cesses of our approach. In Section 3, we present the results of event-driven feature, as well as framework libraries, pose our selected primary publications, along with a preliminary further obstacles for systematic generation of test cases [18]. trend and statistic analysis on those collected publications. Given the variety of challenges in testing Android apps, Later, we introduce our data extraction strategy and their it is important for this field, which has already produced corresponding findings in the following two sections: Sec- a significant amount of approaches, to reflect on what has tion 4 and 5. After that, we discuss the trends we observed already been solved, and on what remains to tackle. To and challenges the community should attempt to address in the best of our knowledge, there is no related literature Section 6 and enumerate the threats to validity of this SLR in review or survey summarizing the topic of Android testing. Section 7. A comparison of this work with literature studies Thus, we attempt to meet this need through a comprehen- is given in Section 8 and finally we conclude this SLR in sive study. Concretely, we undertake a systematic literature Section 9. review (SLR), carefully following the guidelines proposed by Kitchenham et al. [19] and the lessons learned from applying SLR within the software engineering domain by 2 METHODOLOGY OF THIS SLR Brereton et al. [20]. To achieve our goal, we have searched We now introduce the methodology applied in this SLR. We and identified a set of relevant publications from four well- remind the readers that an SLR follows a well-defined strat- known repositories including the ACM Digital Library and egy to systematically identify, examine, synthesize, evaluate from major testing-related venues such as ISSTA, ICSE. and compare all available literature works in a specific topic, Then, we have performed a detailed overview on the current resulting in a reliable and replicable report [19], [21], [22]. state of research in testing Android apps, focusing on the Fig. 2 illustrates the process of our SLR. At the beginning, types and phases of the testing approaches applied as well we define relevant research questions (cf. Section 2.1) to as on a trend analysis in research directions. Eventually, we frame our investigations. The following

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