Modeling and Evaluating Energy Performance of Smartphones

With advances in hardware miniaturization and wireless communication technologies even small portable wireless devices have much communication bandwidth and computing power. These devices include smartphones, tablet computers, and personal digital assistants. Users of these devices expect to run software applications that they usually have on their desktop computers as well as the new applications that are being developed for mobile devices. Web browsing, social networking, gaming, online multimedia playing, global positioning system based navigation, and accessing emails are examples of a few popular applications. Mobile versions of thousands of desktop applications are already available in mobile application markets, and consequently, the expected operational time of smartphones is rising rapidly. At the same time, the complexity of these applications is growing in terms of computation and communication needs, and there is a growing demand for energy in smartphones. However, unlike the exponential growth in computing and communication technologies, in terms of speed and packaging density, battery technology has not kept pace with the rapidly growing energy demand of these devices. Therefore, designers are faced with the need to enhance the battery life of smartphones. Knowledge of how energy is used and lost in the system components of the devices is vital to this end. With this view, we focus on modeling and evaluating the energy performance of smartphones in this thesis. We also propose techniques for enhancing the energy efficiency and functionality of smartphones. The detailed contributions of the thesis are as follows: (i) we present a nite state machine based model to estimate the energy cost of an application running on a smartphone, and provide practical approaches to extract model parameters; (ii) the concept of energy cost pro le is introduced to assess the impact of design decisions on energy cost at an early stage of software design; (iii) a generic architecture is proposed and implemented for enhancing the capabilities of smartphones by sharing resources; (iv) we have analyzed the Internet tra c of smartphones to observe the energy saving potentials, and have studied the implications on the existing energy saving techniques; and nally, (v) we have provided a methodology to select user level test cases for performing energy cost evaluation of applications. All of our concepts and proposed methodology have been validated with extensive measurements on a real test bench. Our work contributes to both theoretical understanding of energy e ciency of software applications and practical methodologies for evaluating energy e ciency. In summary, the results of this work can be used by application developers to make implementation level decisions that affect the energy efficiency of software applications on smartphones. In addition, this work leads to the design and implementation of energy e cient smartphones

Improvements of and Extensions to FSMWeb: Testing Mobile Apps

A mobile application is a software program that runs on mobile device. In 2017, 178.1 billion mobile apps downloaded and the number is expected to grow to 258.2 billion app downloads in 2022 [19]. The number of app downloads poses a challenge for mobile application testers to find the right approach to test apps. This dissertation extends the FSMWeb approach for testing web applications [50] to test mobile applications (FSMApp). During the process of analyzing FSMWeb how it could be extended to test Mobile Apps, a number of shortcomings were detected which we improved upon. We discuss these first. We present an approach to generate black-box tests to test fail-safe behavior for web applications. We apply the approach to a large commercial web application. The approach uses a functional (behavioral) model to generate tests. It then determines at which states in the execution of behavioral test failures can occur and what mitigation requirements need to be tested. Mitigation requirements are used to build mitigation models for each failure type. From those mitigation models failure mitigation tests are generated. Next, this dissertation provides an approach for selective black-box model-based fail-safe regression testing for web applications. It classifies existing tests and test requirements as reusable, retestable, and obsolete. Removing reusable test requirements reduces test requirements between 49% to 65% in the case study. The approach also uses partial regeneration for new tests wherever possible. Third, we present the new FSMApp approach to test mobile applications and compare the approach with several other approaches [88, 37]. A number of case studies explore applicability, scalability, effectiveness, and efficiency of FSMApp with other approaches. Future work makes suggestion on how to improve test generation and execution efficiency with FSMApp