Chandra Shekhar Maddila

According to our database, Chandra Shekhar Maddila authored at least 28 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

AI-Assisted Code Authoring at Scale: Fine-Tuning, Deploying, and Mixed Methods Evaluation.

Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan, Peter C. Rigby

Proc. ACM Softw. Eng., 2024

Moving Faster and Reducing Risk: Using LLMs in Release Deployment.

Rui Abreu, Vijayaraghavan Murali, Peter C. Rigby, Chandra Shekhar Maddila, Weiyan Sun, Jun Ge, Kaavya Chinniah, Audris Mockus, Megh Mehta, Nachiappan Nagappan

CoRR, 2024

AI-Assisted SQL Authoring at Industry Scale.

Chandra Shekhar Maddila, Negar Ghorbani, Kosay Jabre, Vijayaraghavan Murali, Edwin Kim, Parth Thakkar, Nikolay Pavlovich Laptev, Olivia Harman, Diana Hsu, Rui Abreu, Peter C. Rigby

CoRR, 2024

Multi-line AI-Assisted Code Authoring.

Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar, Peter C. Rigby, Andy Chiu, Imad Ahmad, Arun Ganesan, Chandra Shekhar Maddila, Vijayaraghavan Murali, Ali Tayyebi, Nachiappan Nagappan

Proceedings of the Companion Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering, 2024

2023

Nudge: Accelerating Overdue Pull Requests toward Completion.

Chandra Shekhar Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen

ACM Trans. Softw. Eng. Methodol., April, 2023

Improving Code Reviewer Recommendation: Accuracy, Latency, Workload, and Bystanders.

Peter C. Rigby, Seth Rogers, Sadruddin Saleem, Parth Suresh, Daniel Suskin, Patrick Riggs, Chandra Shekhar Maddila, Nachiappan Nagappan

CoRR, 2023

CodeCompose: A Large-Scale Industrial Deployment of AI-assisted Code Authoring.

Vijayaraghavan Murali, Chandra Shekhar Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan

CoRR, 2023

Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations at Microsoft.

Jiyang Zhang, Chandra Shekhar Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen

Proceedings of the 45th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2023

2022

Recommender Systems for DevOps.

Chandra Shekhar Maddila

PhD thesis, 2022

ConE: A Concurrent Edit Detection Tool for Large-scale Software Development.

Chandra Shekhar Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen

ACM Trans. Softw. Eng. Methodol., 2022

A Tale of Two Cities: Software Developers Working from Home during the COVID-19 Pandemic.

Denae Ford, Margaret-Anne D. Storey, Thomas Zimmermann, Christian Bird, Sonia Jaffe, Chandra Shekhar Maddila, Jenna L. Butler, Brian Houck, Nachiappan Nagappan

ACM Trans. Softw. Eng. Methodol., 2022

Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations.

Jiyang Zhang, Chandra Shekhar Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen

CoRR, 2022

Nalanda: a socio-technical graph platform for building software analytics tools at enterprise scale.

Chandra Shekhar Maddila, Suhas Shanbhogue, Apoorva Agrawal, Thomas Zimmermann, Chetan Bansal, Nicole Forsgren, Divyanshu Agrawal, Kim Herzig, Arie van Deursen

Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022

What are Weak Links in the npm Supply Chain?

Nusrat Zahan, Thomas Zimmermann, Patrice Godefroid, Brendan Murphy, Chandra Shekhar Maddila, Laurie A. Williams

Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: Software Engineering in Practice, 2022

2021

The SPACE of Developer Productivity: There's more to it than you think.

Nicole Forsgren, Margaret-Anne D. Storey, Chandra Shekhar Maddila, Thomas Zimmermann, Brian Houck, Jenna L. Butler

ACM Queue, 2021

Nalanda: A Socio-Technical Graph for Building Software Analytics Tools at Enterprise Scale.

Chandra Shekhar Maddila, Apoorva Agrawal, Thomas Zimmermann, Nicole Forsgren, Kim Herzig, Arie van Deursen

CoRR, 2021

ConE: A Concurrent Edit Detection Tool for Large ScaleSoftware Development.

Chandra Shekhar Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen

CoRR, 2021

The SPACE of developer productivity.

Nicole Forsgren, Margaret-Anne D. Storey, Chandra Shekhar Maddila, Thomas Zimmermann, Brian Houck, Jenna L. Butler

Commun. ACM, 2021

2020

Nudge: Accelerating Overdue Pull Requests Towards Completion.

Chandra Shekhar Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen

CoRR, 2020

Studying Ransomware Attacks Using Web Search Logs.

Chetan Bansal, Pantazis Deligiannis, Chandra Shekhar Maddila, Nikitha Rao

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Rex: Preventing Bugs and Misconfiguration in Large Services Using Correlated Change Analysis.

Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, Chetan Bansal, Chandra Shekhar Maddila, Balasubramanyan Ashok, Sumit Asthana, Christian Bird, Aditya Kumar

Proceedings of the 17th USENIX Symposium on Networked Systems Design and Implementation, 2020

Product Insights: Analyzing Product Intents in Web Search.

Nikitha Rao, Chetan Bansal, Subhabrata Mukherjee, Chandra Shekhar Maddila

Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

2019

Predicting pull request completion time: a case study on large scale cloud services.

Chandra Shekhar Maddila, Chetan Bansal, Nachiappan Nagappan

Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019

WhoDo: automating reviewer suggestions at scale.

Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Christian Bird, Chetan Bansal, Chandra Shekhar Maddila, Sonu Mehta, Balasubramanyan Ashok

Proceedings of the ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2019

FastLane: test minimization for rapidly deployed large-scale online services.

Adithya Abraham Philip, Ranjita Bhagwan, Rahul Kumar, Chandra Shekhar Maddila, Nachiappan Nagappan

Proceedings of the 41st International Conference on Software Engineering, 2019

Building sankie: an AI platform for DevOps.

Rahul Kumar, Chetan Bansal, Chandra Shekhar Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava

Proceedings of the 1st International Workshop on Bots in Software Engineering, 2019

2018

Orca: Differential Bug Localization in Large-Scale Services.

Ranjita Bhagwan, Rahul Kumar, Chandra Shekhar Maddila, Adithya Abraham Philip

Proceedings of the 13th USENIX Symposium on Operating Systems Design and Implementation, 2018

2017

Estimating Code-Switching on Twitter with a Novel Generalized Word-Level Language Detection Technique.

Shruti Rijhwani, Royal Sequiera, Monojit Choudhury, Kalika Bali, Chandra Shekhar Maddila

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017