Hello World!

I work for Facebook / Meta. Before that, I was at Microsoft Research. My work lies in the intersection of software engineering (SE), developer productivity, and machine learning (ML). My recent research has focused on large-scale software repository mining, building distributed data platforms and services that enable applications of ML and information retrieval (IR) for solving software engineering problems.

I also work on understanding developer productivity, empirical software engineering, and understanding the impact of smart recommenders on developer productivity and software development processes. My work has resulted in tech transfers and generated measurable impact on engineering velocity and developer productivity across Microsoft. I also enjoy publishing my work in top-tier conferences and journals in SE, systems, and IR domains.

I was a PhD student at the Software Engineering Research Group (SERG) @ TU-Delft, advised by Prof. Arie van Deursen.

AWARDS, INVITED TALKS, MEDIA

Winner of Jay Lepreau best paper award in USENIX OSDI (2018).
Invited talk on differential bug localization (ORCA) at USENIX Annual technical Conference (ATC). USENIX ATC '19 - Orca: Differential Bug Localization in Large-Scale Services
My work (Nudge) is featured in prestigious tech magazine VentureBeat. Microsoft's Nudge service leverages AI to speed up completion of pull requests | VentureBeat
My work (SPACE framework) is featured in Business Insider , InfoQ, and GitHub official blog.
My work (MEC) is featured in Time magazine – the best inventions of 2021.
My work (Sankie) is featured in prestigious Microsoft Research Podcast series. Podcast: Can we make better software by using ML and AI techniques? With Chandra Maddila and Chetan Bansal - Microsoft Research
Invited talk on AIOps in continuous software engineering. University of Victoria. AIOps in Continuous Software Engineering: A Q&A with Chandra Maddila
Invited talk on Machine learning for software engineering (ML4SE). Delft university of Technology.

Publications and Patents

Chandra Maddila, Negar Ghorbani, Kosay Jabre, Vijayaraghavan Murali, Edwin Kim, Parth Thakkar, Nikolay Pavlovich Laptev, Olivia Harman, Diana Hsu, Rui Abreu, Peter C Rigby: AI-Assisted SQL Authoring at Industry Scale. arxiv [paper]
Vijayaraghavan Murali, Chandra Maddila, Imad Ahmad, Michael Bolin, Daniel Cheng, Negar Ghorbani, Renuka Fernandez, Nachiappan Nagappan, Peter C Rigby: AI-assisted Code Authoring at Scale: Fine-tuning, deploying, and mixed methods evaluation. FSE 2024 [paper]
Omer Dunay, Daniel Cheng, Adam Tait, Parth Thakkar, Peter C Rigby, Andy Chiu, Imad Ahmad, Arun Ganesan, Chandra Maddila, Vijayaraghavan Murali, Ali Tayyebi, Nachiappan Nagappan: Multi-line AI-assisted Code Authoring. FSE 2024 [paper]
Peter C Rigby, Seth Rogers, Sadruddin Saleem, Parth Suresh, Daniel Suskin, Patrick Riggs, Chandra Maddila, Nachiappan Nagappan: Improving code reviewer recommendation: Accuracy, latency, workload, and bystanders. arxiv [paper]
Jiyang Zhang, Chandra Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen (first two authors contributed equally): Using Large-scale Heterogeneous Graph Representation Learning for Code Review Recommendations. ICSE 2023 [paper]
Denae Ford, Margaret-Anne D. Storey, Thomas Zimmermann, Christian Bird, Sonia Jaffe, Chandra Shekhar Maddila, Jenna L. Butler, Brian Houck, Nachiappan Nagappan: A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic. ICSE 2022 (journal first) [paper]
Nusrat Zahan, Laurie Williams, Thomas Zimmermann, Patrice Godefroid, Brendan Murphy, Chandra Maddila: What are Weak Links in the npm Supply Chain? ICSE 2022 [paper]
Chandra Maddila, Apoorva Agrawal, Thomas Zimmermann, Nicole Forsgren, Kim Herzig, Arie van Deursen: Nalanda: A Socio-Technical Graph for Building Software Analytics Tools at Enterprise Scale. FSE 2022 [paper]
Chandra Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen: ConE: A Concurrent Edit Detection Tool for Large ScaleSoftware Development (TOSEM) [paper]
Nicole Forsgren, Margaret Anne Storey, Chandra Maddila, Thomas Zimmermann, Brian Houck, Jenna Butler: The SPACE of Developer Productivity: There's more to it than you think. {Volume 19, January-February 2021}, Association for Computing Machinery (ACM). ACM Queue. This is one of the top downloaded ACM papers with 161K downloads in ten months. [paper]
Jaime Teevan, Brent Hecht, Sonia Jaffe, Nancy Baym, Rachel Bergmann, Matt Brodsky, Bill Buxton, Jenna Butler, Adam Coleman, Mary Czerwinski, Brian Houck, Ginger Hudson, Shamsi Iqbal, Chandra Maddila, Kate Nowak, Emily Peloquin, Ricardo Reyna Fernandez, Sean Rintel, Abigail Sellen, Tiffany Smith, Margaret-Anne Storey, Siddharth Suri, Hana Wolf, Longqi Yang: The New Future of Work: Research from Microsoft into the Pandemic’s Impact on Work Practices. TOSEM [paper]
Denae Ford, Margaret-Anne D. Storey, Thomas Zimmermann, Christian Bird, Sonia Jaffe, Chandra Shekhar Maddila, Jenna L. Butler, Brian Houck, Nachiappan Nagappan: A Tale of Two Cities: Software Developers Working from Home During the COVID-19 Pandemic. TOSEM [paper]
Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen: Nudge: Accelerating Overdue Pull Requests Towards Completion (TOSEM) [paper]
Nikitha Rao, Chetan Bansal, Subhabrata Mukherjee, Chandra Shekhar Maddila: Product Insights: Analyzing Product Intents in Web Search. CIKM 2020 [paper]
Chetan Bansal, Pantazis Deligiannis, Chandra Shekhar Maddila, Nikitha Rao: Studying Ransomware Attacks Using Web Search Logs. SIGIR 2020 [paper]
Sonu Mehta, Ranjita Bhagwan, Rahul Kumar, Chetan Bansal, Chandra Maddila, B Ashok, Sumit Asthana, Christian Bird, Aditya Kumar: Rex: Preventing Bugs and Misconfiguration in Large Services Using Correlated Change Analysis. USENIX NSDI 2020 [paper]
Sumit Asthana, Rahul Kumar, Ranjita Bhagwan, Christian Bird, Chetan Bansal, Chandra Maddila, Sonu Mehta, B. Ashok: WhoDo: automating reviewer suggestions at scale. ESEC/SIGSOFT FSE 2019 [paper]
Chandra Maddila, Chetan Bansal, Nachiappan Nagappan: Predicting pull request completion time: a case study on large scale cloud services. ESEC/SIGSOFT FSE 2019 [paper]
Rahul Kumar, Chetan Bansal, Chandra Shekhar Maddila, Nitin Sharma, Shawn Martelock, Ravi Bhargava: Building sankie: an AI platform for DevOps. BotSE@ICSE 2019 [paper]
Adithya Abraham Philip, Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Nachiappan Nagappan: FastLane: test minimization for rapidly deployed large-scale online services. ICSE 2019 [paper]
Ranjita Bhagwan, Rahul Kumar, Chandra Maddila, Adithya Abraham Philip (author names are listed in the order of last names): ORCA: Differential Bug Localization in Large-Scale Services. OSDI 2018. Jay Lepreau best paper award [paper]
Shruti Rijhwani, Royal Sequiera, Monojit Choudhury, Kalika Bali, Chandra Maddila: Estimating Code-Switching on Twitter with a Novel Generalized Word-Level Language Detection Technique. ACL 2017 [paper]
Detecting Misconfiguration and/or Bug (s) in Large Service (s) Using Correlated Change Analysis, USPTO App 16515135 (patent)
ConE: A Concurrent Edit Detection Tool for Large Scale Software Development (patent under filing with USPTO)

Interns

Divyanshu Agrawal Research intern (Fall, 2021). Research Engineer at Microsoft Research.
Jiyang Zhang Research intern (Summer, 2021). PhD student at the University of Texas at Austin.
Suhas Shanbhogue Research intern (Summer, 2021). Software Engineer at Microsoft.
Ujjwal Raizada Research intern (Spring, 2021). Software engineer at Google.
Sai Surya Upadrasta Research intern (Spring, 2020). Software engineer at Google.
Sumit Asthana Research Fellow (2017-2019). PhD student at the University of Michigan Ann Arbor.
Adithya Philip Research Fellow (2017-2019). PhD student at Carnegie Mellon University.