Test Model and Coverage Analysis for Location-based Mobile Services

Abstract

Abstract-Location-based services (LBS) are very important mobile app services, which provide diverse mobility services for mobile users anywhere and anytime. This brings new demands, issues, and challenges in mobile application testing. Today, mobile applications provide location-based service functions based on dynamic location contexts, mobile users and their travel patterns to deliver location-based mobile data, and service actions. Current software testing methods do not consider location-based validation coverage. Hence, there is a lack of research results addressing location-based mobile application testing. This paper focuses on mobile LBS testing. A novel test object model is proposed for quality validation of location-based mobile information services. In addition, the related test coverage metrics are also presented. These metrics can be useful for test engineers in designing test cases. A case study based on student testers is reported to demonstrate the potential application of the proposed model.

Automated Testing of Android Apps: A Systematic Literature Review

“…The literature includes several contributions on highlighting issues related to the performance of Android apps such as poor responsiveness [29] and exception handling [55]. Yang et al [74], for example, have proposed a systematic testing approach to uncover and quantify common causes of poor [27] MAMBA [28] Pretect [29] SSDA [30] TrimDroid [8] ERVA [9] SAPIENZ [11] RacerDroid [31] DiagDroid [32] MOTIF [33] DRUN [34] GAT [35] Zhang et al [36] Jabbarvand et al [37] Qian et al [38] Ermuth et al [39] Zhang et al [40] Zhang et al [41] dLens [42] Packeviius et al [43] Knorr et al [44] IntentDroid [45] Farto et al [46] Bielik et al [47] MobiGUITAR [48] Aktouf et al [49] AppAudit [50] Hassanshahi et al [51] iMPAcT [52] Deng et al [53] Espada et al [54] Zhang et al [55] QUANTUM [56] CRAXDroid [57] IntentFuzzer [58] Vikomir et al [59] Shahriar et al [60] APSET [61] DROIDRACER [62] AppACTS [63] CAFA [64] Guo et al…”

“…It re-executes all the unit test cases every time when a piece of code is changed. As an example, Hu et al [84] have applied unit testing to [26] CRASHSCOPE [27] MAMBA [28] Pretect [29] DroidMate [93] SSDA [30] TrimDroid [8] ERVA [9] Clapp et al [10] SAPIENZ [11] RacerDroid [31] Baek et al [94] DiagDroid [32] MobiPlay [95] MOTIF [33] DRUN [34] DroidDEV [96] GAT [35] Zhang et al [36] Jabbarvand et al [37] Qian et al [38] Ermuth et al [39] Cadage [97] Zhang et al [40] Zhang et al [41] dLens [42] Sonny et al [98] Packeviius et al [43] SIG-Droid [99] Knorr et al [44] TAST [100] IntentDroid [45] Griebe et al [101] Farto et al [46] Bielik et al [47] MobiGUITAR [48] AGRippin [102] Aktouf et al [49] THOR [103] AppAudit [50] Morgado et al [104] Hassanshahi et al [51] iMPAcT [52] Deng et al [53] Espada et al…”

“…Table 5 summarises the aforementioned test phases, where the most recurrently applied testing phase is system testing (accounting for nearly 80% of the selected publications), followed by unit testing and integration testing, respectively. [26] CRASHSCOPE [27] MAMBA [28] Pretect [29] DroidMate [93] SSDA [30] TrimDroid [8] ERVA [9] Clapp et al [10] SAPIENZ [11] RacerDroid [31] Baek et al [94] DiagDroid [32] MobiPlay [95] MOTIF [33] DRUN [34] DroidDEV [96] GAT [35] Zhang et al [36] Jabbarvand et al [37] Qian et al [38] Ermuth et al [39] Cadage [97] Zhang et al [40] Zhang et al [41] dLens [42] Sonny et al [98] Packeviius et al…”

“…Table 9 enumerates the coverage metrics used in the literature, where LoC appears to be the most concerned metric. [40] Bug dLens [42], TEMA [123], Hu et al [84], MobiGUITAR [48] Defect APSET [61] Fault QUANTUM [56], Vikomir et al [59], Sonny et al [98] Crash Shahriar et al [60], Caiipa [107], .CRASHSCOPE [27] Vulnerability Sadeh et al [124], IntentDroid [45] Leakage CRAXDroid [57], Yang et al [58] Ground Truth refers to a reference dataset where each element is labelled. In this SLR, we consider two types of ground truths.…”

How to Test Location-based Mobile Apps

“…We have proposed an initial test model [17] and some test coverage metrics [18] for function services of mobile LBS. In this paper, we present some test strategies about selecting test devices, location context, location objects, and moving patterns.…”