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Research Projects

Literature about design suggests that a variety of alternatives leads to a higher quality final design. When software designers, either individually or together, are designing in front of the whiteboard, they rarely explore different solution alternatives. How can we help designers to explore more design alternatives for software problems? To achieve this, we are working on a process to facilitate designers to collaborate and produce high quality software designs while considering more solution alternatives.

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Project Dates: 
April 2015

One method of facilitating developers to understand the complex inner nature of software that we have employed is the use of information visualization. Software is often so complex that even the developers who initially created it cannot understand all of the possible runtime behaviors that it can exhibit --- specifically, all of the bugs that it may contain. In order to present large code bases with innumerable characteristics and relationships of its components (e.g., instructions, variables, values, and timings) we have developed a number of novel visualizations of software.

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May 2001

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.

Project Dates: 
January 2017

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 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.

Project Dates: 
August 2011

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

The dynamic nature of markets wherein business relationships are established and dissolved continuously demands systems that can cope with constant change, and do so with security paramount. These relationships are reified as services  that are offered by organizations and used  within a spectrum of domains and use contexts. Current service technologies fail to meet the requirements, however; interfaces are rigid, non-secure, and “one-size-fits-all solutions” which hardly meet the demands of any of its users.

Project Dates: 
July 2007

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