A mobile application has been developed to be used for assistance in crisis scenarios. To assure the application is dependable enough to be used in such scenarios, the application was put under test. This thesis investigates different approaches to functional testing and security testing. Five common methods of generating test cases for functional testing have been identified and four were applied on the application. The coverage achieved for each method was measured and compared. For this specific application under test, test cases from a method called decision table-testing scored the highest code coverage. 9 bugs related to functionality were identified. Fuzz testing is a simple security testing technique for efficiently finding security flaws, and was applied for security testing of our application. During the fuzz test, system security properties were breached. An unauthorized user could read and alter asset data, and it also affected the system's availability. Our overall conclusion was that with more time, creating functional tests for smaller components of the application might have been more effective in finding faults and achieving coverage.

This work introduces three new coverage criteria based on combinatorial-based event and element sequences that occur in the mobile environment. The novel combinatorial-based criteria are used to reduce, prioritize, and generate test suites for mobile applications. The combinatorial-based criteria include unique coverage of events and elements with different respects to ordering. For instance, consider the coverage of a pair of events, e1 and e2. The least strict criterion, Combinatorial Coverage (CCov), counts the combination of these two events in a test case without respect to the order in which the events occur. That is, the combination (e1, e2) is the same as (e2, e1). The second criterion, Sequence-Based Combinatorial Coverage (SCov), considers the order of occurrence within a test case. Sequences (e1, ..., e2) and (e2,..., e1) are different sequences. The third and strictest criterion is Consecutive-Sequence Combinatorial Coverage (CSCov), which counts adjacent sequences of consecutive pairs. The sequence (e1, e2) is only counted if e1 immediately occurs before e2. The first contribution uses the novel combinatorial-based criteria for the purpose of test suite reduction. Empirical studies reveal that the criteria, when used with event sequences and sequences of size t=2, reduce the test suites by 22.8%-61.3% while the reduced test suites provide 98.8% to 100% fault finding effectiveness. Empirical studies in Android also reveal that the event sequence criteria of size t=2 reduce the test suites by 24.67%-66% while losing at most 0.39% code coverage. When the criteria are used with element sequences and sequences of size t=2, the test suites are reduced by 40\% to 72.67%, losing less than 0.87% code coverage. The second contribution of this work applies the combinatorial-based criteria for test suite prioritization of mobile application test suites. The results of an empirical study show that the prioritization criteria that use element and event sequences cover the test suite's elements, events, and code faster than random orderings. On average the prioritized orderings cover all elements within 21.81% of the test suite, all events within 45.99% of the test suite, and all code within 51.21% of the test suite. Random orderings achieve full code coverage with 84.8% of the test suite on average. The third contribution uses the combinatorial-based criteria for test suite generation. This work modifies the random walk tool used from prior experiments to give weight (preference) to coverage of the combinatorial-based event and element criteria. The use of Element SCov and CSCov criteria result in test suites that increase code coverage for three of the four subject applications. Specifically, the code coverage increases by 0.29%-5.89% with SCov and 1.36%-6.79% with CSCov in comparison to the original random walk algorithm. The SCov criterion increases total sequence coverage by 5%-88% and the CSCov criterion increases sequence coverage by 13%-68%. One criteria, Element CCov, failed to increase code coverage for two of the four applications. The contributions of this dissertation show that the novel combinatorial-based criteria using sequences of events and elements offer improvements to different testing strategies for mobile applications, including test suite reduction, prioritization, and generation.

Background. With the development and popularization of mobile Internet, smartphones are becoming more and more popular. Android is one of the most popular platforms of smartphones.  And application is one of the most important part of a smartphone. There are a lot of money and human resources spent on Android application development every year. And quiet a big part of them goes to quality assurance of applications. Graphic user interface (GUI) testing is one important part of its quality assurance. Android phones use touch screen as the major I/O method. Therefore, GUI testing on android platform shall be different to conventional software applications that are designed to run on desktop environment. Objectives. The aim of this research is to assess the performance of two GUI testing approaches (2nd vs 3rd generation) of automated UI testing in terms of testing Android applications. By assessing these approaches, we could hopefully get insights of their advantages and limitations for using them in the context of Android development. And this aim can be divided into three objectives, to compare the time spent on implementing test cases of each tool, to compare the time costed when executing test cases of each tool, to compare the number of defects found by each tool. Methods. The research methodology we chose is controlled experiment. We have chosen UI Automator and Appium to represent 2nd generation GUI testing approach, EyeAutomate and SikuliX to represent 3rd generation GUI testing approach. We used each tool to implement and execute 120 test cases to compare them on the time spent on implementing test cases of each tool, the time costed when executing test cases of each tool, the number of real defects found by each tool, and the number of false positives found by each tool. Results. Tools using 3rd generation GUI testing approach take less time to implement test cases than tools using 2nd generation GUI testing approach. And there is no specific pattern when comparing tools using 2nd and 3rd generation GUI testing approaches in terms of time cost on executing test cases. It is different between different test cases. Besides false positive alerts appear at a much higher frequency in tools using 3rd generation GUI testing approach than tools using 2nd generation GUI testing approach. While, real defects found by each tool are the same. Conclusions. 3rd generation GUI testing approach is more efficient in terms of implementing test cases than 2nd generation GUI testing approach. But 3rd generation GUI testing approach finds much more false positives than 2nd generation approach. To decide if a defect alert is false positive or not requires human effort. In a long term, it may accumulate huge lost on human efforts. Therefore, to maintain test cases, 3rd generation approach consumes lots of human efforts.

Automated test generation for Andriod apps with reinforcement learning algorithms often produce test suites with redundant coverage. We looked at minimizing test suites that have already been generated based on state–action–reward–state–action (SARSA) algorithms. In this dissertation, we hypothesize that there is room for improvement by introducing novel hybrid approaches that combine SARSA-generated test suites with greedy reduction algorithms following the principle of Head-up Guidance System (HGS™) approach. In addition, we apply an empirical study on Android test suites that reveals the value of these new hybrid methods. Our novel approaches focus on post-processing test suites by applying greedy reduction algorithms. To reduce Android test suites, we utilize different coverage criteria including event-based criterion (EBC), element-based criterion (ELBC), and combinatorial-based sequences criteria (CBSC) that follow the principle of combinatorial testing to generate sequences of events and elements. The proposed criteria effectively decreased the test suites generated by SARSA and revealed a high performance in maintaining code coverage. These findings suggest that test suite reduction using these criteria is particularly well suited for SARSA-generated test suites of Android apps.

Software Quality is a key concern for any companies working with software development. This is true due to the fact that the success of any software directly depends on Quality of software. It is expected that the software is of best quality for a long duration of time. With the introduction of Mobile applications the task of maintaining the quality of an application has been difficult and have faced many challenges. Many companies working with mobile application have reformed their process in order to maintain the quality of their application. The introduction of Automation testing in the test process is one such reform that have changed the face of mobile application testing in today’s world. This work deals with the concepts of Automation System testing for the mobile application which is until now a new thing and it has many things yet to be explored. The approach to automation testing is simple yet unique for the department of PT-MT/Quality Management in Robert Bosch GmbH based in Leinfelden, Stuttgart. Over here a selection and implementation of a test framework will be done for Automation testing of the mobile Applications that are being developed. For this a requirement specification document is being created which will form the basis for selecting a framework from the KT Analysis table. Finally, a framework TestComplete will be implemented for the already developed application "PLR measure&go" The implementation will include all the procedure required to set up the test framework as a part of documentation. The framework TestComplete will be used to create System test for iOS and Android operation system. Lastly the execution of test and the Result reporting is being shown as a complete process for Automation testing.

Software Quality is a key concern for any companies working with software development. This is true due to the fact that the success of any software directly depends on Quality of software. It is expected that the software is of best quality for a long duration of time. With the introduction of Mobile applications the task of maintaining the quality of an application has been difficult and have faced many challenges. Many companies working with mobile application have reformed their process in order to maintain the quality of their application. The introduction of Automation testing in the test process is one such reform that have changed the face of mobile application testing in today’s world. This work deals with the concepts of Automation System testing for the mobile application which is until now a new thing and it has many things yet to be explored. The approach to automation testing is simple yet unique for the department of PT-MT/Quality Management in Robert Bosch GmbH based in Leinfelden, Stuttgart. Over here a selection and implementation of a test framework will be done for Automation testing of the mobile Applications that are being developed. For this a requirement specification document is being created which will form the basis for selecting a framework from the KT Analysis table. Finally, a framework TestComplete will be implemented for the already developed application "PLR measure&go" The implementation will include all the procedure required to set up the test framework as a part of documentation. The framework TestComplete will be used to create System test for iOS and Android operation system. Lastly the execution of test and the Result reporting is being shown as a complete process for Automation testing.

This dissertation introduces a hybrid strategy for automated testing of Android applications that combines reinforcement learning and test suite prioritization. These approaches aim to improve the effectiveness of the testing process by employing reinforcement learning algorithms, namely Q-learning and SARSA (State-Action-Reward-State-Action), for automated test case generation. The studies provide compelling evidence that reinforcement learning techniques hold great potential in generating test cases that consistently achieve high code coverage; however, the generated test cases may not always be in the optimal order. In this study, novel test case prioritization methods are developed, leveraging pairwise event interactions coverage, application state coverage, and application activity coverage, so as to optimize the rates of code coverage specifically for SARSA-generated test cases. Additionally, test suite prioritization techniques are introduced based on UI element coverage, test case cost, and test case complexity to further enhance the ordering of SARSA-generated test cases. Empirical investigations demonstrate that applying the proposed test suite prioritization techniques to the test suites generated by the reinforcement learning algorithm SARSA improved the rates of code coverage over original orderings and random orderings of test cases.