Information Needs for Software Development Analytics.

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Bibliographic Details
Title:	Information Needs for Software Development Analytics.
Authors:	Buse, Raymond P. L.¹ buse@cs.virginia.edu, Zimmermann, Thomas tzimmer@microsoft.com
Source:	ICSE: International Conference on Software Engineering. Feb2012, p987-996. 10p.
Subjects:	Computer software development, Computer programming management, Software engineering, Computer software, Data security, Database security, Computer security
Abstract:	Software development is a data rich activity with many sophisticated metrics. Yet engineers often lack the tools and techniques necessary to leverage these potentially powerful information resources toward decision making. In this paper, we present the data and analysis needs of professional software engineers, which we identified among 110 developers and managers in a survey. We asked about their decision making process, their needs for artifacts and indicators, and scenarios in which they would use analytics. The survey responses lead us to propose several guidelines for analytics tools in software development including: Engineers do not necessarily have much expertise in data analysis; thus tools should be easy to use, fast, and produce concise output. Engineers have diverse analysis needs and consider most indicators to be important; thus tools should at the same time support many different types of artifacts and many indicators. In addition, engineers want to drill down into data based on time, organizational structure, and system architecture. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Software development is a data rich activity with many sophisticated metrics. Yet engineers often lack the tools and techniques necessary to leverage these potentially powerful information resources toward decision making. In this paper, we present the data and analysis needs of professional software engineers, which we identified among 110 developers and managers in a survey. We asked about their decision making process, their needs for artifacts and indicators, and scenarios in which they would use analytics. The survey responses lead us to propose several guidelines for analytics tools in software development including: Engineers do not necessarily have much expertise in data analysis; thus tools should be easy to use, fast, and produce concise output. Engineers have diverse analysis needs and consider most indicators to be important; thus tools should at the same time support many different types of artifacts and many indicators. In addition, engineers want to drill down into data based on time, organizational structure, and system architecture. [ABSTRACT FROM AUTHOR]