A test case generation approach for mobile APPS based on context and GUI events

The increase of mobile devices with rich innovative feature has become an enabler for developing mobile applications (mobile apps) that offer users an advance and extremely-localized context-aware content. Nowadays mobile apps are developed to address more critical areas of people’s daily computing needs, which bring concern on the applications’ quality. In order to build a high quality and more reliable applications, there is a need for effective testing techniques to test the apps. The most recent testing technique focuses on graphical user interface (GUI) events with little attention to context events. This makes it difficult to identify other defects in the changes that can be inclined by context in which an application runs. The major challenge in testing mobile apps that react to context events is how to identify the events from an application during testing. This study proposes an approach (named TEGDroid) for testing mobile apps considering the two sets of events: GUI and context events. This approach comprises five steps which are; extraction of resources from APK file, static analysis of the extracted app’s byte code to identify GUI events, analysis of mobile apps’ permission to identify different scenarios of context events, generation of test case based on the GUI and context events and validation of the test cases using code coverage and mutation testing. Experiment was performed on real world open source mobile apps to evaluate TEGDroid. Results from the experimental evaluation indicates that the approach is effective in identifying context events and had 61%-91% coverage across the seven (7) selected applications. Results from the mutation analysis shows that 100% of the mutants were killed. This indicates that TEGDroid have the capability to detect faults in mobile apps

TEGDroid: Test Case Generation Approach for Android Apps Considering Context and GUI Events

The advancement in mobile technologies has led to the production of mobile devices (e.g. smartphone) with rich innovative features. This has enabled the development of mobile applications that offer users an advanced and extremely localized context-aware content. The recent dependence of people on mobile applications for various computational needs poses a significant concern on the quality of mobile applications. In order to build a high quality and more reliable applications, there is a need for effective testing techniques to test the applications. Most existing testing technique focuses on GUI events only without sufficient support for context events. This makes it difficult to identify other defects in the changes that can be inclined by context in which an application runs. This paper presents an approach named TEGDroid for generating test case for Android Apps considering both context and GUI Events. The GUI and context events are identified through the static analysis of bytecode, and the analysis of app’s permission from the XML file. An experiment was performed on real world mobile apps to evaluate TEGDroid. Our experimental results show that TEGDroid is effective in identifying context events and had 65%-91% coverage across the eight selected applications. To evaluate the fault detection capability of this approach, mutation testing was performed by introducing mutants to the applications. Results from the mutation analysis shows that 100% of the mutants were killed. This indicates that TEGDroid have the capability to detect faults in mobile apps

AMOGA: A Static-Dynamic Model Generation Strategy for Mobile Apps Testing

In the past few years, mobile devices have been increasingly replacing traditional computers, as their capabilities, such as CPU computation, memory, RAM size, and many more, are being enhanced almost to the level of conventional computers. These capabilities are being exploited by mobile apps developers to produce apps that offer more functionalities and optimized performance. To ensure acceptable quality and to meet their specifications (e.g., design), mobile apps need to be tested thoroughly. As the testing process is often tedious, test automation can be the key to alleviating such laborious activities. In the context of the Android-based mobile apps, researchers and practitioners have proposed many approaches to automate the testing process mainly on the creation of the test suite. Although useful, most existing approaches rely on reverse engineering a model of the application under test for test case creation. Often, such approaches exhibit a lack of comprehensiveness, as the application model does not capture the dynamic behavior of the applications extensively due to the incompleteness of reverse engineering approaches. To address this issue, this paper proposes AMOGA, a strategy that uses a hybrid, static-dynamic approach for generating a user interface model from mobile apps for model-based testing. AMOGA implements a novel crawling technique that uses the event list of UI element associated with each event to dynamically exercise the events ordering at the run time to explore the applications’ behavior. An experimental evaluation was performed to assess the effectiveness of our strategy by measuring the code coverage and the fault detection capability through the use of mutation testing concept. The results of the experimental assessment showed that AMOGA represents an alternative approach for model-based testing of mobile apps by generating comprehensive models to improve the coverage of the applications. The strategy proved its effectiveness by achievin..

Beta-Lactam Resistance Profile of E. Coli Isolated from Urinary Tract Infection Patients in Selected Hospitals within Gusau Metropolis

The emergence of antibiotic resistance, particularly beta-lactam resistance, poses a significant challenge in the management of urinary tract infections (UTIs) caused by Escherichia coli (E. coli). This study aimed to investigate the beta-lactam resistance profile of E. coli isolated from UTI patients in selected hospitals within the Gusau metropolis. A total of 92 urine samples were collected from UTI patients attending selected hospitals in Gusau metropolis. Isolation and identification of E. coli were conducted using standard microbiological techniques. Antibiotic susceptibility testing was performed using the disc diffusion method according to Clinical and Laboratory Standards Institute (CLSI) guidelines. Furthermore, phenotypic confirmation of beta-lactam resistance was carried out using double disc synergy testing (DDST).  Out of 92 urine samples obtained from patients with UTIs, E. coli was identified in 19 samples (20.7%), out of the 19 E. coli isolates, ESBL production was detected in 9 (47.36%) based on the results of the DDST, and among the E. coli isolates tested, 12 (63.16%) exhibited resistance to beta-lactam (Ceftriaxone), while 5 (26.31%) showed intermediate susceptibility, and 2 (10.53%) were susceptible to this antibiotic. Results revealed a concerning prevalence of beta-lactam resistance among E. coli isolates, highlighting the urgent need for effective antimicrobial stewardship and infection control measures in the region

An Assessment of Ovarian Cancer Histotypes Across the African Diaspora

ObjectiveOvarian cancer in Black women is common in many West African countries but is relatively rare in North America. Black women have worse survival outcomes when compared to White women. Ovarian cancer histotype, diagnosis, and age at presentation are known prognostic factors for outcome. We sought to conduct a preliminary comparative assessment of these factors across the African diaspora. MethodsPatients diagnosed with ovarian cancer (all histologies) between June 2016-December 2019 in Departments of Pathology at 25 participating sites in Nigeria were identified. Comparative population-based data, inclusive of Caribbean-born Blacks (CBB) and US-born Blacks (USB), were additionally captured from the International Agency for Research on Cancer and Florida Cancer Data Systems. Histology, country of birth, and age at diagnosis data were collected and evaluated across the three subgroups: USB, CBB and Nigerians. Statistical analyses were done using chi-square and student's t-test with significance set at pResultsNigerians had the highest proportion of germ cell tumor (GCT, 11.5%) and sex-cord stromal (SCST, 16.2%) ovarian cancers relative to CBB and USB (p=0.001). CBB (79.4%) and USB (77.3%) women were diagnosed with a larger proportion of serous ovarian cancer than Nigerians (60.4%) (p<0.0001). Nigerians were diagnosed with epithelial ovarian cancers at the youngest age (51.7 +/- 12.8 years) relative to USB (58.9 +/- 15.0) and CBB (59.0 +/- 13.0,p<0.001). Black women [CBB (25.2 +/- 15.0), Nigerians (29.5 +/- 15.1), and USB (33.9 +/- 17.9)] were diagnosed with GCT younger than White women (35.4 +/- 20.5, p=0.011). Black women [Nigerians (47.5 +/- 15.9), USB (50.9 +/- 18.3) and CBB (50.9 +/- 18.3)] were also diagnosed with SCST younger than White women (55.6 +/- 16.5, p<0.01). ConclusionThere is significant variation in age of diagnosis and distribution of ovarian cancer histotype/diagnosis across the African diaspora. The etiology of these findings requires further investigation