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Software Performance Project


The mission of the Software Performance project is to strengthen the scientific foundations of software performance measurement ("metrology for IT"). 


Its goals are:

  • Application: Replace unreliable common practices with rigorously-studied methods grounded in design of experiments
  • Research: Solve measurement challenges created by the evolution and increased complexity of commodity hardware
  • Transfer: Feed improved methods back into the community of practice

Major Accomplishments:

  • qdfca (Quick-Deploy Formal Concept Analysis) is a command-line filter that implements Formal Concept Analysis (FCA). It is small, scriptable, and easy to install, with no external requirements other than the standard Ruby library.
  • Test Suite for Validating Application Profiling Tools, Version 1.2
  • Test Driver for Android, Version 1.0 (RTD automates the repeated launching of Android test apps for experimental data collection.) 
  • R package bootBCa, Version 1.0
    This package provides a function to find confidence intervals using Efron's nonparametric bias-corrected and accelerated (BCa) bootstrap method. It is an enhanced derivative of the function bcanon, forked from bootstrap_2012.04-1. Adaptive determination of the number of bootstrap replications is supported and the amount of memory required is less by a factor of nboot.
  • The Gem for Experimental Computer Science (GECS) is for managing the data resulting from experiments on software and IT systems. It realizes a data model that disambiguates the vocabulary of experimentation and measurement for a computer science audience. It also provides convenience functions to determine confidence intervals, analyze main effects and interactions, and export data in an R-compatible format for further analysis and visualization.


Lead Organizational Unit:



David Flater
National Institute of Standards and Technology
Software and Systems Division, Mail Stop 8970
Gaithersburg, MD 20899

William F. Guthrie
National Institute of Standards and Technology
Statistical Engineering Division, Mail Stop 8980
Gaithersburg, MD 20899

Project Alumni:

Vreda Pieterse
Ramón Luis De Jesús