The number of mobile applications has increased drastically in the past few years. A recent study has shown that reusing source code is a common practice for Android application development. However, reuse in mobile applications is not necessarily limited to the source code (i.e., program logic). User interface (UI) design plays a vital role in constructing the user-perceived quality of a mobile application. The user-perceived quality reflects the users' opinions of a product. For mobile applications, it can be quantified by the number of downloads and raters. In this study, we extract commonly used UI elements, denoted as Common Element Sets (CESs), from user interfaces of applications. Moreover, we highlight the characteristics of CESs that can result in a high user-perceived quality by proposing various metrics. Through an empirical study on 1292 mobile applications, we observe that (i) CESs of mobile applications widely occur among and across different categories; (ii) certain characteristics of CESs can provide a high user-perceived quality; and (iii) through a manual analysis, we recommend UI templates that are extracted and summarized from CESs for developers. Developers and quality assurance personnel can use our guidelines to improve the quality of mobile applications. (C) 2016 Elsevier Inc. All rights reserved.

The number of mobile applications has increased drastically in the past few years. Some applications are superior to the others in terms of user-perceived quality. User-perceived quality can be defined as the user's opinion of a product. For mobile applications, it can be quantified by the number of downloads and ratings. Earlier studies suggested that user interface (UI) barriers (i.e., input or output challenges) can affect the user-perceived quality of mobile applications. In this paper, we explore the relation between UI complexity and user-perceived quality in Android applications. Furthermore, we strive to provide guidelines for the proper amount of UI complexity that helps an application achieve high user-perceived quality through an empirical study on 1,292 mobile applications in 8 different categories.

Bug prediction models are often used to help allocate software quality assurance efforts. Software metrics (e.g., process metrics and product metrics) are at the heart of bug prediction models. However, some of these metrics like churn are not actionable, on the contrary, antipatterns which refer to specific design and implementation styles can tell the developers whether a design choice is "poor" or not. Poor designs can be fixed by refactoring. Therefore in this paper, we explore the use of antipatterns for bug prediction, and strive to improve the accuracy of bug prediction models by proposing various metrics based on antipatterns. An additional feature to our proposed metrics is that they take into account the history of antipatterns in files from their inception into the system. Through a case study on multiple versions of Eclipse and ArgoUML, we observe that (i) files participating in antipatterns have higher bug density than other files, (ii) our proposed antipattern based metrics can provide additional explanatory power over traditional metrics, and (iii) improve the F-measure of cross-system bug prediction models by 12.5% in average. Managers and quality assurance personnel can use our proposed metrics to better improve their bug prediction models and better focus testing activities and the allocation of support resources.