Recent introduction of a dynamic permission model in Android, allowing the users to grant and revoke permissions a at the installation of an app, has made it much harder to properly test apps. Since an app's behavior may change depending on the granted permissions, it needs to be tested under a wide range of granted permission combinations.
This research addresses challenges in understanding and developing lightweight, Web-based informal music education environments that bring the complexity and joy of orchestral music to diverse audiences. The challenges span from providing awareness and appreciation of different classical music genres through creation of multi-instrument musical compositions, in ways that are fun and interactive.
Previous studies have shown that there is a non-trivial amount of duplication in source code. We analyzed a corpus of 2.6 million non-fork projects hosted on GitHub representing over 258 million files written in Java, C++ Python and JavaScript. We found that this corpus has a mere 54 million unique files. In other words, 79% of the code on GitHub consists of clones of previously created files. There is considerable variation between language ecosystems. JavaScript has the highest rate of file duplication, only 7% of the files are distinct.
The current security mechanisms for Android apps, both static and dynamic analysis approaches, are insufficient for detection and prevention of the increasingly dynamic and sophisticated security attacks.
We developed techniques for clustering of failures. Failure-clustering techniques attempt to categorize failing test cases according to the bugs that caused them. Test cases are clustered by utilizing their execution profiles (gathered from instrumented versions of the code) as a means to encode the behavior of those executions. Such techniques can offer suggestions for duplicate submissions of bug reports.
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.
In addition to the dynamic nature of software while executing, this dynamism extends to the evolution of the software's code itself. The software's evolution is often captured in its entirety by revision-control systems (such as CVS, Subversion, and Git). By utilizing this rich artifact, as well as other historical artifacts (e.g., bug-tracking systems and mailing lists), we can offer a number of techniques for recommending future actions to developers.
The utility of a smartphone is limited by its battery capacity and the ability of its hardware and software to efficiently use the device’s battery. To properly characterize the energy consumption of an app and identify energy defects, it is critical that apps are properly tested, i.e., analyzed dynamically to assess the app’s energy properties. However, currently there is a lack of testing tools for evaluating the energy properties of apps. We present COBWEB, a search-based energy testing technique for Android.
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