Current Projects

Current research and projects by students

 

Ahmed Al-Zubidy (aalzubidy@crimson.ua.edu)
Supervisor: Dr. Jeffrey Carver

Currently working on two researches, the first one is is studying the barriers in the searching phase of the systematic literature review process in software engineering. As the process have been widely accepted and used, it is still have issues, some of those issues regarding the search of the literature in the process. I am studying those search related barriers, designing studies, and solutions to help making the process less costly in time and effort.
The second project an evaluation of the evaluation methods that are used in computer science education. Reviewing literature from different sources and evaluating the used methods in order to provide set of guidelines or checklist that help building evaluation studies in computer science education field.


Elizabeth Williams (eawilliams2@crimson.ua.edu)
Supervisor: Dr. Jeff Gray

My research is in social network analysis.  I have created GeoContext, a system that discovers trending topics in social media and analyzes where those topics are centered geographically.  GeoContext can provide real-time, detailed information about topics such as traffic, airport delays, and current events.


Morgan Burcham (mburcham@crimson.ua.edu)

Supervisor: Dr. Jeffrey Carver

Performing a systematic literature review of security publications to determine if such literature is presented in a scientific way to encourage theory building, replications, etc. to further contributions to a growing body of knowledge in the field.


Wenhua Hu (whu10@crimson.ua.edu)
Supervisor: Dr. Jeffrey Carver

My research is focused on Empirical Software Engineering. The detail research study is about applying human errors in the software requirement engineering. The main purpose of this project is to collecting all kinds of human errors that can happen in the software requirement stages though literature review, and then to build a human error taxonomy help researchers and practitioners identify or prevent the related errors in their document and thus improve the softwarequality. For the structured error taxonomy, we will design several empirical studies to validate it.