The demand for analyzing large scale telemetry, machine, and quality data is rapidly
increasing in software industry. Data scientists are becoming popular within software teams …

Context: Over the last decade, Agile methods have changed the software development
process in an unparalleled way and with the increasing popularity of Big Data, optimizing …

AIOps is about empowering software and service engineers (eg, developers, program
managers, support engineers, site reliability engineers) to efficiently and effectively build …

Creating and running software produces large amounts of raw data about the development
process and the customer usage, which can be turned into actionable insight with the help of …

In this paper, we present the results from two surveys related to data science applied to
software engineering. The first survey solicited questions that software engineers would like …

Purpose The purpose of this essay is to illustrate how project management “pull” and AI or
analytics technology “push” are likely to result in incremental and disruptive evolution of …

Background After many years of research on software repositories, the knowledge for
building mature, reusable tools that perform data retrieval, storage and basic analytics is …

The Art and Science of Analyzing Software Data provides valuable information on analysis
techniques often used to derive insight from software data. This book shares best practices …

Large software organizations are transitioning to event data platforms as they culturally shift
to better support data-driven decision making. This paper offers a case study at Microsoft …

In recent years, more and more traditional shrink-wrapped software is provided as 7x24
online services. Incidents (events that lead to service disruptions or outages) could affect …