Title :
Analytics-Driven Dashboards Enable Leading Indicators for Requirements and Designs of Large-Scale Systems
Author :
Selby, Richard W.
Author_Institution :
Northrop Grumman Space Technol., Univ. of Southern California, Los Angeles, CA
Abstract :
Mining software repositories using analytics-driven dashboards provides a unifying mechanism for understanding, evaluating, and predicting the development, management, and economics of large-scale systems and processes. Dashboards enable measurement and interactive graphical displays of complex information and support flexible analytic capabilities for user customizability and extensibility. Dashboards commonly include system requirements and design metrics because they provide leading indicators for project size, growth, and volatility. This article focuses on dashboards that have been used on actual large-scale software projects as well as example empirical relationships revealed by the dashboards. The empirical results focus on leading indicators for requirements and designs of large-scale software systems based on insights from two sets of software projects containing 14 systems and 23 systems.
Keywords :
data mining; software engineering; analytics-driven dashboards; interactive graphical displays; large-scale systems; software repositories mining; Displays; Economic forecasting; Information analysis; Large scale integration; Large-scale systems; Project management; Risk management; Software development management; Software performance; Technology management; defects; designs; empirical analysis; leading indicators; metrics; requirements;
Journal_Title :
Software, IEEE
