[PAST EVENT] Mario Linares-Vasquez, Computer Science, Dissertation Proposal

October 5, 2015
3pm - 4:30pm
McGlothlin-Street Hall, Room 002
251 Jamestown Rd
Williamsburg, VA 23185Map this location
Mobile developers and testers face a number of emerging challenges. These include rapid platform evolution and API instability; issues in bug reporting and reproduction involving complex multitouch gestures; platform fragmentation; the impact of reviews and ratings on the success of their apps; management of crowd-sourced requirements; continuous pressure from the market for frequent releases; lack of effective and usable testing tools; and limited computational resources for handheld devices. Traditional and contemporary methods in software evolution and maintenance were not designed for these types of challenges, therefore, a set of studies and a new toolbox of techniques for mobile development are required to analyze current challenges and propose new solutions.

This proposal presents a set of empirical studies, as well as solutions, for some of the key challenges when evolving and maintaining Android apps. In particular, the focus of this proposal is on studying and supporting/improving (i) Android API instability, (ii) performance optimizations, (iii) automatic GUI testing, and (iv) energy consumption. When carrying out the studies, we relied on qualitative and quantitative analyses to understand the phenomena at large scale by considering evidence extracted from software repositories and the opinions of mobile open- source developers. In particular, we analyzed the impact of Android API instability on apps success and developers reactions as well as current practices of Android developers for detecting and fixing performance bottlenecks.

We also devised novel approaches aimed at supporting testing and energy optimization of mobile apps. First, we propose a novel hybrid approach for automatic GUI-based testing of apps that is able to generate (un)natural test sequences by mining real applications usages and learning statistical models that represent the GUI interactions. In addition, we propose a model for estimating the energy consumption of Android APIs and detecting energy greedy API usage patterns. Finally, we propose a multi-objective approach for optimizing the energy consumption of GUIs in Android apps that is able to generate visually appealing color compositions, while reducing the energy consumption and keeping a design concept close to the original.

Mario Linares-Vasquez is a Ph.D. candidate at William & Mary advised by Dr. Denys Poshyvanyk. He received his B.S. in Systems Engineering from Universidad Nacional de Colombia in 2005, and his M.S. in Systems Engineering and Computing from Universidad Nacional de Colombia in 2009. His research interests include mobile development, software evolution and maintenance, software architecture, mining software repositories, and application of data mining and machine learning techniques to support software engineering tasks.