Department of Computer Science


Research Experience for Undergraduates

Software and Data Analytics

Software and data analytics is the most widely used technique for ensuring the quality of software systems and solving wide variety of business problems, but many challenging issues are still open for investigation. The sample research projects of this REU project cover the most critical open issues in real-time data analytics, non-testable systems, and evaluation. Any improvement of the techniques and approaches for understanding and addressing these issues could significantly improve the quality of software systems, enhance the quality of predictions, and reduce the cost. The sample projects will investigate the essential techniques of data gathering and data analysis in software analytics. The research results will lead to the improvement of software quality and the advance of software and data analytics. All of our faculty mentors are experts with extensive research experience in both software and data analytics. The research results will be shared with other researchers and practitioners.

Award

Funded by National Science Foundation (NSF), Research Experience for Undergraduates. This is a paid 10-week program, with a $6000 stipend, and an allowance for housing, meals, and travel. This program is hosted at East Carolina University in the Department of Computer Science.

Sample Research Projects

The research focus is in Software and Data Analytics. The sample research projects cover open research topics in software and data analytics including, Code Recommendation for Programming Language Learners; Intelligent Program Update Detection and Automation; Human-Computer Collaborative Dialogue Systems; Using Machine Learning to Estimate Software Development Effort; Understanding Implicit Extension APIs; Machine Learning Algorithms for Biometric Data Analysis; Performance Evaluation of Machine Learning Algorithms. Students participating in these projects will learn about topics including code recommendation systems, static program analysis, program transformation, classical techniques for classification in machine learning (e.g., k-nearest neighbors), deep learning, information retrieval, software testing, software maintenance, software repository mining, software quality metrics, crypto-currencies, and both theoretical and empirical measurements of algorithm performance.

Applicant Qualifications

  • US citizen or permanent resident.
  • GPA of 3.0 or higher.
  • Current undergraduate students in software engineering, computer science, or related majors.
  • Underrepresented groups are strongly encouraged to apply, as well as those from academic institutions with limited research opportunities in STEM.

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