@inproceedings{8dd539e1c38d48bbb926d6324e9d2768,
title = "Nalanda: a socio-technical graph platform for building software analytics tools at enterprise scale",
abstract = "Software development is information-dense knowledge work that requires collaboration with other developers and awareness of artifacts such as work items, pull requests, and file changes. With the speed of development increasing, information overload and information discovery are challenges for people developing and maintaining these systems. Finding information about similar code changes and experts is difficult for software engineers, especially when they work in large software systems or have just recently joined a project. In this paper, we build a large scale data platform named Nalanda platform to address the challenges of information overload and discovery. Nalanda contains two subsystems: (1) a large scale socio-technical graph system, named Nalanda graph system, and (2) a large scale index system, named Nalanda index system that aims at satisfying the information needs of software developers. To show the versatility of the Nalanda platform, we built two applications: (1) a software analytics application with a news feed named MyNalanda that has Daily Active Users (DAU) of 290 and Monthly Active Users (MAU) of 590, and (2) a recommendation system for related work items and pull requests that accomplished similar tasks (artifact recommendation) and a recommendation system for subject matter experts (expert recommendation), augmented by the Nalanda socio-technical graph. Initial studies of the two applications found that developers and engineering managers are favorable toward continued use of the news feed application for information discovery. The studies also found that developers agreed that a system like Nalanda artifact and expert recommendation application could reduce the time spent and the number of places needed to visit to find information. ",
keywords = "Collaborative software development, Empirical study, Recommender Systems for Software Engineering, Socio-Technical Graphs",
author = "Chandra Maddila and Suhas Shanbhogue and Apoorva Agrawal and Thomas Zimmermann and Chetan Bansal and Nicole Forsgren and Divyanshu Agrawal and Kim Herzig and {Van Deursen}, Arie",
year = "2022",
doi = "10.1145/3540250.3558949",
language = "English",
series = "ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering",
publisher = "Association for Computing Machinery (ACM)",
pages = "1246--1256",
editor = "Abhik Roychoudhury and Cristian Cadar and Miryung Kim",
booktitle = "ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering",
address = "United States",
note = "30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, ESEC/FSE 2022 ; Conference date: 14-11-2022 Through 18-11-2022",
}