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Research Projects

One of the most difficult tasks in debugging software for a developer is to understand the nature of the fault. Techniques have been proposed by researchers that can help *locate* the fault, but mostly neglected is a way to describe the nature of the fault. We are developing software models, visualizations, and techniques to aid in the diagnosis of the faults in the software.

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Project Dates: 
August 2011

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.

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Project Dates: 
May 2001

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.

Research Area(s): 
Project Dates: 
August 2011

To enable much of our research to enable program understanding, software quality, and maintenance, we utilize and develop analyses of program code. These analyses model the flows of information through the logic of programs and systems. With these analysis models enable automated techniques to assist development and maintenance tasks.

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Project Dates: 
March 1998

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.

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Project Dates: 
October 2007

Spacetime is a framework for developing time-stepped, multi-worker applications based on the tuplespace model. Workers compute within spacetimed frames -- a fixed portion of the shared data during a fixed period of time. The locally modified data may be pushed back to the shared store at the end of each step.

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Project Dates: 
January 2015

The development of a software system is now ever more frequently a part of a larger development effort, including multiple software systems that co-exist in the same environment: a software ecosystem. Though most studies of the evolution of software have focused on a single software system, there is much that we can learn from the analysis of a set of interrelated systems. Topic modeling techniques show promise for mining the data stored in software repositories to understand the evolution of a system.

Project Dates: 
September 2012

Research shows that sharing one’s location can help people stay connected, coordinate daily activities, and provide a sense of comfort and safety [1]. Recently, smartphones and location-based services (LBS) have become widely available in developed countries [7], but only a small percentage of smartphone users have ever tried sharing lo­cation with other people [8]. Our work aims to understand real-world factors shaping behaviors and attitudes towards social location-sharing, especially in regards to why people avoid or abandon the technology, or limit their usage.

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Project Dates: 
May 2009

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