World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
63
Citations
18829
World Ranking
2725
National Ranking
1355

Research.com Recognitions

  • 2020 - ACM Fellow For contributions to empirical software engineering and data-driven software development
  • 2015 - ACM Distinguished Member

Overview

Nachiappan Nagappan is affiliated with Facebook (United States) in the United States. Their research primarily focuses on the field of Computer Science, with a strong emphasis on Software Engineering and its related subfields.

Their work covers multiple subfields of study including Information Systems, Software, Computer Networks and Communications, Artificial Intelligence, and Computer Science Applications. The main topics addressed in their research include Software Engineering Research, Software System Performance and Reliability, Software Engineering Techniques and Practices, Software Testing and Debugging Techniques, Open Source Software Innovations, Software Reliability and Analysis Research, and Advanced Malware Detection Techniques.

Among their recent publications are:

  • "A Tale of Two Cities: Software Developers Working from Home during the COVID-19 Pandemic" (2021) published in ACM Transactions on Software Engineering and Methodology
  • "Including Everyone, Everywhere: Understanding Opportunities and Challenges of Geographic Gender-Inclusion in OSS" (2021) published in IEEE Transactions on Software Engineering
  • "A Systematic Literature Review on Automated Software Vulnerability Detection Using Machine Learning" (2024) published in ACM Computing Surveys
  • "Large-scale intent analysis for identifying large-review-effort code changes" (2020) published in Information and Software Technology
  • "Feedback-driven semi-supervised synthesis of program transformations" (2020) published in Proceedings of the ACM on Programming Languages

Nachiappan Nagappan frequently publishes in venues such as arXiv (Cornell University), ACM Transactions on Software Engineering and Methodology, Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, OPAL (Open@LaTrobe) (La Trobe University), and Zenodo (CERN European Organization for Nuclear Research).

Their frequent co-authors include Peter C. Rigby, Chandra Maddila, Ayushi Rastogi, David Lo, and Gunnar Kudrjavets.

Awards received by Nachiappan Nagappan include:

  • ACM Fellow (2020) for contributions to empirical software engineering and data-driven software development
  • ACM Distinguished Member (2015)

Best Publications

  • Mining metrics to predict component failures

    Nachiappan Nagappan;Thomas Ball;Andreas Zeller

  • Use of relative code churn measures to predict system defect density

    Nachiappan Nagappan;Thomas Ball

  • Understanding network failures in data centers: measurement, analysis, and implications

    Phillipa Gill;Navendu Jain;Nachiappan Nagappan

  • Software engineering for machine learning: a case study

    Saleema Amershi;Andrew Begel;Christian Bird;Robert DeLine

  • Cross-project defect prediction: a large scale experiment on data vs. domain vs. process

    Thomas Zimmermann;Nachiappan Nagappan;Harald Gall;Emanuel Giger

  • Predicting defects using network analysis on dependency graphs

    Thomas Zimmermann;Nachiappan Nagappan

  • Characterizing cloud computing hardware reliability

    Kashi Venkatesh Vishwanath;Nachiappan Nagappan

  • Don't touch my code!: examining the effects of ownership on software quality

    Christian Bird;Nachiappan Nagappan;Brendan Murphy;Harald Gall

  • Improving the CS1 experience with pair programming

    Nachiappan Nagappan;Laurie Williams;Miriam Ferzli;Eric Wiebe

  • Static analysis tools as early indicators of pre-release defect density

    Nachiappan Nagappan;Thomas Ball

  • On the value of static analysis for fault detection in software

    J. Zheng;L. Williams;N. Nagappan;W. Snipes

  • The influence of organizational structure on software quality: an empirical case study

    Nachiappan Nagappan;Brendan Murphy;Victor Basili

  • Characterizing and predicting which bugs get fixed: an empirical study of Microsoft Windows

    Philip J. Guo;Thomas Zimmermann;Nachiappan Nagappan;Brendan Murphy

  • Usage and Perceptions of Agile Software Development in an Industrial Context: An Exploratory Study

    A. Begel;N. Nagappan

  • Do Crosscutting Concerns Cause Defects

    M. Eaddy;T. Zimmermann;K.D. Sherwood;V. Garg

  • Does distributed development affect software quality?: an empirical case study of Windows Vista

    Christian Bird;Nachiappan Nagappan;Premkumar Devanbu;Harald Gall

  • Can developer-module networks predict failures?

    Martin Pinzger;Nachiappan Nagappan;Brendan Murphy

  • A field study of refactoring challenges and benefits

    Miryung Kim;Thomas Zimmermann;Nachiappan Nagappan

  • HYDRA: Massively Compositional Model for Cross-Project Defect Prediction

    Xin Xia;David Lo;Sinno Jialin Pan;Nachiappan Nagappan

  • Using Software Dependencies and Churn Metrics to Predict Field Failures: An Empirical Case Study

    N. Nagappan;T. Ball

Frequent Co-Authors

Thomas Zimmermann
Thomas Zimmermann Microsoft (United States)
Laurie Williams
Laurie Williams North Carolina State University
Christian Bird
Christian Bird Microsoft (United States)
Brendan Murphy
Brendan Murphy Microsoft (United States)
Mladen A. Vouk
Mladen A. Vouk North Carolina State University
Thomas Ball
Thomas Ball Microsoft (United States)
Harald C. Gall
Harald C. Gall University of Zurich
Premkumar Devanbu
Premkumar Devanbu University of California, Davis
Andreas Zeller
Andreas Zeller Saarland University
David Lo
David Lo Singapore Management University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

As technology continues to shape the workforce, pursuing online degrees in related fields offers flexibility and diverse career opportunities. For those interested in advanced analytics, the best data science masters programs online provide specialized skills highly valued across industries.

Computer Science knowledge also complements fields like project management. A construction management degree online equips professionals with technical and leadership skills for managing complex projects.

For those seeking versatile business expertise, the most affordable online mba programs allow working professionals to enhance their credentials and leadership potential without breaking the bank.

If speed is a priority, numerous one year graduate programs offer accelerated pathways to earn a respected credential and kickstart new careers fast.

Exploring these online degree options can broaden your career prospects, strengthen interdisciplinary skills, and open doors to dynamic opportunities both within and beyond Computer Science.

Best Scientists Citing Nachiappan Nagappan

Trending Scientists