Search Results for author: Chandra Maddila

Found 7 papers, 0 papers with code

Studying Ransomware Attacks Using Web Search Logs

no code implementations1 May 2020 Chetan Bansal, Pantazis Deligiannis, Chandra Maddila, Nikitha Rao

Cyber attacks are increasingly becoming prevalent and causing significant damage to individuals, businesses and even countries.

Product Insights: Analyzing Product Intents in Web Search

no code implementations18 May 2020 Nikitha Rao, Chetan Bansal, Subhabrata Mukherjee, Chandra Maddila

Web search engines are frequently used to access information about products.

Nudge: Accelerating Overdue Pull Requests Towards Completion

no code implementations25 Nov 2020 Chandra Maddila, Sai Surya Upadrasta, Chetan Bansal, Nachiappan Nagappan, Georgios Gousios, Arie van Deursen

The key novelty of Nudge is that it succeeds in reducing pull request resolution time, while ensuring that developers perceive the notifications sent as useful, at the scale of thousands of repositories.

Action Detection Activity Detection

ConE: A Concurrent Edit Detection Tool for Large Scale Software Development

no code implementations16 Jan 2021 Chandra Maddila, Nachiappan Nagappan, Christian Bird, Georgios Gousios, Arie van Deursen

We study half a year of changes made to six large repositories in Microsoft in which at least 1, 000 pull requests are created each month.

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

no code implementations4 Feb 2022 Jiyang Zhang, Chandra Maddila, Ram Bairi, Christian Bird, Ujjwal Raizada, Apoorva Agrawal, Yamini Jhawar, Kim Herzig, Arie van Deursen

Code review is an integral part of any mature software development process, and identifying the best reviewer for a code change is a well-accepted problem within the software engineering community.

Graph Representation Learning Management +1

Multi-line AI-assisted Code Authoring

no code implementations6 Feb 2024 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

In this paper, we present how we scaled the product from displaying single-line suggestions to multi-line suggestions.

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