I am an undergraduate junior at the University of Delaware. I have a major in computer science and a minor in business administration. My technical interests include product management, natural language processing and machine learning.
I have been researching at UD's Software Analysis and Compilation Research lab for almost two years now. After briefly working on a project with two graduate students, I changed my focus and started up a new project. Under the supervision and mentorship of Dr. Lori Pollock and Dr. Vijay Shanker, my research centers around using natural language processing and machine learning techniques to obtain detailed information about code segments present on question and answer forums.
*to be presented at the Fourth International Workshop on Software Mining and published in the proceedings of the 2015 IEEE/ACM 30th International Conference on Automated Software Engineering Workshops (ASEW 2015)
Abstract In addition to learning good practices and reusing code from mining code examples, programmers can be supported in their learning and code improvement processes through negative, or poorly written, code examples. While it is challenging to identify negative code examples automatically from within source code, we leverage a key insight that the natural language in questions that include code examples posted on forums can provide adequate clues. In this paper, we describe an automatic sentiment analysis-based technique for mining negative code examples from developer question and answer forums along with a technique to automatically mine negative sentiment indicators commonly used by developers, which are used to drive the sentiment-based technique.
