My sabbatical leave was conducted during Spring semester 2014. The leave was successful because it strengthened my research in data mining and software engineering domains and resulted four full-paper publications in peer-reviewed international conferences and one journal paper (to be submitted to a peer-reviewed journal). The purpose of my sabbatical was to complete two main projects: (1) Investigate the stability and defect prediction model performance of feature selection techniques together on real-world software metrics data and (2) Design a novel, robust, and efficient metric selection method for imbalanced data
This dataset is extracted and synthesized from 49 primary studies which related to unsupervised def...
Context: In every software development method, requirement gathering and analysis phase plays the mo...
This study presents the application of the item response theory (IRT) and classification algorithms ...
During my sabbatical leave (Fall 2013), I have mainly worked on the project to explore the dynamics ...
I will share my experience of launching a series of research projects during my sabbatical leave. I ...
I plan to use my sabbatical time creating live websites/ databases/ web services for not-for-profit ...
In business, and especially in troubling economic times, the effective management of software develo...
As new technology rapidly changes the construction industry, we feel it is imperative that our progr...
Detecting defects in software at the bleeding edge of a software development life cycle is vital. Id...
This dataset is about a systematic review of unsupervised learning techniques for software defect pr...
Context: Software defect prediction plays a crucial role in estimating the most defect-prone compone...
The number of research papers on defect prediction has sharply increased for the last decade or so. ...
R markdown files and raw data for our meta-analysis of software defect prediction studies.This is th...
The mining of software repositories has provided significant advances in a multitude of software eng...
The mining of software repositories has provided significant advances in a multitude of software eng...
This dataset is extracted and synthesized from 49 primary studies which related to unsupervised def...
Context: In every software development method, requirement gathering and analysis phase plays the mo...
This study presents the application of the item response theory (IRT) and classification algorithms ...
During my sabbatical leave (Fall 2013), I have mainly worked on the project to explore the dynamics ...
I will share my experience of launching a series of research projects during my sabbatical leave. I ...
I plan to use my sabbatical time creating live websites/ databases/ web services for not-for-profit ...
In business, and especially in troubling economic times, the effective management of software develo...
As new technology rapidly changes the construction industry, we feel it is imperative that our progr...
Detecting defects in software at the bleeding edge of a software development life cycle is vital. Id...
This dataset is about a systematic review of unsupervised learning techniques for software defect pr...
Context: Software defect prediction plays a crucial role in estimating the most defect-prone compone...
The number of research papers on defect prediction has sharply increased for the last decade or so. ...
R markdown files and raw data for our meta-analysis of software defect prediction studies.This is th...
The mining of software repositories has provided significant advances in a multitude of software eng...
The mining of software repositories has provided significant advances in a multitude of software eng...
This dataset is extracted and synthesized from 49 primary studies which related to unsupervised def...
Context: In every software development method, requirement gathering and analysis phase plays the mo...
This study presents the application of the item response theory (IRT) and classification algorithms ...