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.
TrimDroid is a novel combinatorial approach for generating GUI system tests for Android apps.
TrimDroid is comprised of four major components: Model Extraction, Dependency Extraction, Sequence Generation, and Test-Case Generation. Together, these components produce a significantly smaller number of test cases than exhaustive combinatorial technique, yet achieve a comparable coverage.
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.
Given the availability of large-scale source-code repositories, there have been a large number of applications for clone detection. Unfortunately, despite a decade of active research, there is a marked lack in clone detectors that scale to large software repositories. In particular for detecting near-miss clones where significant editing activities may take place in the cloned code.
We developed a fault-localization technique that utilized correlation-based heuristics. The technique and tool was called Tarantula. Tarantula uses the pass/fail statuses of test cases and the events that occurred during execution of each test case to offer the developer recommendations of what may be the faults that are causing test-case failures. The intuition of the approach is to find correlations between execution events and test-case outcomes --- those events that correlate most highly with failure are suggested as places to begin investigation.
This research focuses on techniques for identifying and reducing the costs, streamlining the process, and improving the readiness of future workforce for the acquisition of complex software systems. Emphasis is directed at identifying, tracking, and analyzing software component costs and cost reduction opportunities within acquisition life cycle of open architecture (OA) systems, where such systems combine best-of-breed software components and software products lines (SPLs) that are subject to different intellectual property (IP) license requirements.
In order to produce effective fault-localization, debugging, failure-clustering, and test-suite maintenance techniques, researchers would benefit from a deeper understanding of how faults (i.e., bugs) behave and interact with each other. Some faults, even if executed, may or may not propagate to the output, and even still may or may not influence the output in a way to cause failure. Furthermore, in the presence of multiple faults, faults may interact in a way to obscure each other or in a way to produce behavior not seen in their isolation.
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.
ISR
