Automating Test Case Generation for Android Applications using Model-based Testing

Testing of mobile applications (apps) has its quirks as numerous events are required to be tested. Mobile apps testing, being an evolving domain, carries certain challenges that should be accounted for in the overall testing process. Since smartphone apps are moderate in size so we consider that model-based testing (MBT) using state machines and statecharts could be a promising option for ensuring maximum coverage and completeness of test cases. Using model-based testing approach, we can automate the tedious phase of test case generation, which not only saves time of the overall testing process but also minimizes defects and ensures maximum test case coverage and completeness. In this paper, we explore and model the most critical modules of the mobile app for generating test cases to ascertain the efficiency and impact of using model-based testing. Test cases for the targeted model of the application under test were generated on a real device. The experimental results indicate that our framework reduced the time required to execute all the generated test cases by 50%. Experimental setup and results are reported herein

A systematic approach to generate test cases based on combinations of information

Software based systems incrementally provide critical services to users. Mobile telephone systems, for example, are used in circumstances in which the malfunctioning may have disastrous consequences. During the last years, software has been incorporated in devices used in daily life, such as audio and television. The diversity of systems in which software is incorporated is increasing. Thus, the software development process has to consider a variety of speci ¯cation techniques and models, incorporating also techniques from engineering sciences. In particular, the validation and veri¯cation processes have to be adapted to these new developments. For example, the testing based solely on the software speci¯cation is incomplete. First, there is an implicit objective to verify that the program works correctly (as in the testing model of the 1957{1978, [GH88]). Myers [Mye83] says that with the aim of demonstrating that a program does not fail, we can unconsciously select data that has a low probability of exposing faults. On the other hand, if the objective is to demonstrate that a program has faults, test data will have a higher probability of revealing them. In specification-based testing we select data for which the desired behavior for the system is defined. As stated by Boris Beizer [Bei95] testing should include both clean and dirty tests. Dirty tests are designed to \break" the software; clean tests are designed to demonstrate that software executes correctly. Specifications only provide clean tests.Eje: Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI

A systematic approach to generate test cases based on combinations of information

Software based systems incrementally provide critical services to users. Mobile telephone systems, for example, are used in circumstances in which the malfunctioning may have disastrous consequences. During the last years, software has been incorporated in devices used in daily life, such as audio and television. The diversity of systems in which software is incorporated is increasing. Thus, the software development process has to consider a variety of speci ¯cation techniques and models, incorporating also techniques from engineering sciences. In particular, the validation and veri¯cation processes have to be adapted to these new developments. For example, the testing based solely on the software speci¯cation is incomplete. First, there is an implicit objective to verify that the program works correctly (as in the testing model of the 1957{1978, [GH88]). Myers [Mye83] says that with the aim of demonstrating that a program does not fail, we can unconsciously select data that has a low probability of exposing faults. On the other hand, if the objective is to demonstrate that a program has faults, test data will have a higher probability of revealing them. In specification-based testing we select data for which the desired behavior for the system is defined. As stated by Boris Beizer [Bei95] testing should include both clean and dirty tests. Dirty tests are designed to \break" the software; clean tests are designed to demonstrate that software executes correctly. Specifications only provide clean tests.Eje: Ingeniería de Software y Base de DatosRed de Universidades con Carreras en Informática (RedUNCI

A test case generation framework based on UML statechart diagram

Early software fault detection offers more flexibility to correct errors in the early development stages. Unfortunately, existing studies in this domain are not sufficiently comprehensive in describing the major processes of the automated test case generation. Furthermore, the algorithms used for test case generation are not provided or well described. Current studies also hardly address loops and parallel paths issues, and achieved low coverage criteria. Therefore, this study proposes a test case generation framework that generates minimized and prioritized test cases from UML statechart diagram with higher coverage criteria. This study, conducted a review of the previous research to identify the issues and gaps related to test case generation, model-based testing, and coverage criteria. The proposed framework was designed from the gathered information based on the reviews and consists of eight components that represent a comprehensive test case generation processes. They are relation table, relation graph, consistency checking, test path minimization, test path prioritization, path pruning, test path generation, and test case generation. In addition, a prototype to implement the framework was developed. The evaluation of the framework was conducted in three phases: prototyping, comparison with previous studies, and expert review. The results reveal that the most suitable coverage criteria for UML statechart diagram are all-states coverage, all-transitions coverage, alltransition-pairs coverage, and all-loop-free-paths coverage. Furthermore, this study achieves higher coverage criteria in all coverage criteria, except for all-state coverage, when compared with the previous studies. The results of the experts’ review show that the framework is practical, easy to implement due to it is suitability to generate the test cases. The proposed algorithms provide correct results, and the prototype is able to generate test case effectively. Generally, the proposed system is well accepted by experts owing to its usefulness, usability, and accuracy. This study contributes to both theory and practice by providing an early alternative test case generation framework that achieves high coverage and can effectively generate test cases from UML statechart diagrams. This research adds new knowledge to the software testing field, especially for testing processes in the model-based techniques, testing activity, and testing tool support

Achieving Cost-Effective Software Reliability Through Self-Healing

Heterogeneity, mobility, complexity and new application domains raise new software reliability issues that cannot be met cost-effectively only with classic software engineering approaches. Self-healing systems can successfully address these problems, thus increasing software reliability while reducing maintenance costs. Self-healing systems must be able to automatically identify runtime failures, locate faults, and find a way to bring the system back to an acceptable behavior. This paper discusses the challenges underlying the construction of self-healing systems with particular focus on functional failures, and presents a set of techniques to build software systems that can automatically heal such failures. It introduces techniques to automatically derive assertions to effectively detect functional failures, locate the faults underlying the failures, and identify sequences of actions alternative to the failing sequence to bring the system back to an acceptable behavior