The rising popularity of mobile apps deployed on battery-constrained devices underlines the need for effectively evaluating their energy properties. However, currently there is a lack of testing tools for evaluating the energy properties of apps. As a result, for energy testing, developers are relying on tests intended for evaluating the functional correctness of apps. Such tests may not be adequate for revealing energy defects and inefficiencies in apps.
We are on the cusp of a major opportunity: software tools that take advantage of Big Code. Specifically, Big Code will enable novel tools in areas such as security enhancers, bug finders, and code synthesizers. What do researchers need from Big Code to make progress on their tools? Our answer is an infrastructure that consists of 100,000 executable Java programs together with a set of working tools and an environment for building new tools.
Sustainability has become a pressing concern, especially given the looming effects of climate change. Sustainable development aims to meet current needs while ensuring sustainability of natural systems and the environment so as to not compromise the ability of future generations to meet their own needs. Current software engineering methods, however, do not explicitly support sustainability or sustainable development.
We developed a token-based approach for large scale code clone detection which is based on a filtering heuristic that reduces the number of token comparisons when the two code blocks are compared. We also developed a MapReduce based parallel algorithm that uses the filtering heuristic and scales to thousands of projects. The filtering heuristic is generic and can also be used in conjunction with other token-based approaches. In that context, we demonstrated how it can increase the retrieval speed and decrease the memory usage of the index-based approaches.
The Internet of Things (IoT) is an emerging technology powered by smart devices that increasingly pervades our environments and practices. The process of incorporating technology into one's practices involves use and adaptation of the technology and is usually referred to as appropriation. In research about IoT, appropriation of IoT technology is a rather new topic. It is necessary to understand how appropriation takes place in order to be able to provide strong support for it in the design of technology.
Sourcerer is an ongoing research project at the University of California, Irvine aimed at exploring open source projects through the use of code analysis. The existence of an extremely large body of open source code presents a tremendous opportunity for software engineering research. Not only do we leverage this code for our own research, but we provide the open source Sourcerer Infrastructure and curated datasets for other researchers to use.
The Sourcerer Infrastructure is composed of a number of layers.
Microtask crowdsourcing systems such as FoldIt and ESP partition work into short, self-contained microtasks, reducing barriers to contribute, increasing parallelism, and reducing the time to complete work. Could this model be applied to software development? To explore this question, we are designing a development process and cloud-based IDE for crowd development.
DELDroid is an automated system for determination of least privilege architecture in Android and its enforcement at runtime. A key contribution of our approach is the ability to limit the privileges granted to apps without the need to modify them.
DELDroid utilizes static program analysis techniques to extract the exact privileges each component needs for providing its functionality. A Multiple-Domain Matrix representation of the system's architecture is then used to automatically analyze the security posture of the system and derive its least-privilege architecture.
ISR
