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Raghu N Kacker (Fed)

Raghu Kacker is a scientist in the Applied and Computational Mathematics Division (ACMD) of the Information Technology Laboratory (ITL) of the National Institute of Standards and Technology (NIST). His current interests include combinatorial methods for black box testing and their applications; mathematics of metrology; quantification of uncertainty in measurements from physical experiments and computational models.

Current Projects:

Additional Data:

Awards

  • Fellow, American Society for Quality ASQ (2000)
  • Fellow, American Statistical Association ASA (1994)
  • U.S. Department of Commerce Silver Medal (2014)
  • U.S. Department of Commerce Bronze Medal (1994)
  • Distinguished Technical Staff Award, AT&T-Bell Laboratories (1985)
  • Federal Laboratory Consortium Award for combinatorial testing tool (2009)R&D 100 Award, Team Member for developing the software S-check (1997)
  • PATENT:  United States Patent number: US 10,552,300 B2. Date: February 4, 2020. Title: Oracle-free match testing of a program using covering arrays and equivalence classes. Owner: U.S. Department of Commerce. Inventors: D. Richard Kuhn and Raghu N. Kacker.

Selected Publications

Laleh S. Ghandehari, Yu Lei, Raghu N. Kacker, D. Richard Kuhn, Tao Xie, and David Kung. A Combinatorial Testing-Based Approach to Fault Localization, IEEE Transactions on Software Engineering, 46 (June 2020) pp. 616-645.  https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8438933

Jin Chu Wu, Alvin F. Martin and Raghu N. Kacker. Bootstrap variability studies in ROC analysis on large datasets, Communications in Statistics - Simulation and Computation, 43 (2014) pp. 225-236. https://doi.org/10.1080/03610918.2012.700362

Yu Lei, Raghu N. Kacker, D. Richard Kuhn, Vadim Okun, and James F. Lawrence. IPOG/IPOG-D: Efficient test generation for multi-way combinatorial testing, Software Testing, Verification and Reliability, 18 (2007) pp. 125-148.  https://doi.org/10.1002/stvr.381

Raghu N. Kacker and James F. Lawrence. Trapezoidal and triangular distributions for Type B evaluation of standard uncertainty, Metrologia, 44 (2007) pp. 117-127. https://iopscience.iop.org/volume/0026-1394/44

Karl K. Irikura, Russell D. Johnson, and Raghu N. Kacker. Uncertainties in scaling factors for ab-initio vibrational frequencies, Journal of Physical Chemistry A, 109 (2005) pp. 8430-8437. https://doi.org/10.1021/jp052793n

Raghu N. Kacker and Albert T. Jones. On use of Bayesian statistics to make Guide to the expression of uncertainty in measurement consistent, Metrologia, 40 (2003), pp. 235-248.  https://iopscience.iop.org/journal/0026-1394

Raghu N. Kackar. Off-line Quality Control, Parameter Design, and the Taguchi Method, with discussion and response, Journal of Quality Technology, 17 (1985), pp. 176-209.  https://doi.org/10.1080/00224065.1985.11978964

Raghu N. Kackar and David A. Harville. Approximations for Standard Errors of Estimators of Fixed and Random Effects in mixed Linear Models” Journal of American Statistical Association, 79 (1984), pp. 853-862. https://www.jstor.org/stable/pdf/2288715.pdf

Publications

A unified model of core metrological concepts

Author(s)
David W. Flater, Raghu N. Kacker, Douglas Foxvog
The definitions of core metrological terms, especially quantity, quantity value, and unit, have been the subject of years of wrangling in standards

On Combinatorial Security Testing for the Tor Anonymity Network Client

Author(s)
Dimitris Simos, Bernhard Garn, Dominik-Philip Schreiber, Manuel Leithner, D. Richard Kuhn, Raghu N. Kacker
In this paper, we present an application of combinatorial security testing to the well-known anonymity network Tor. Rigorous testing of the Tor network is

Combinatorial testing for building reliable systems

Author(s)
M S Raunak, D. Richard Kuhn, Raghu N. Kacker, Yu Lei
Combinatorial testing is an approach where test suites are developed by efficiently covering interactions of parameter values and configuration settings

Patents (2018-Present)

Oracle-Free Match Testing of a Program Using Covering Arrays and Equivalence Classes

NIST Inventors
D. Richard Kuhn and Raghu N Kacker
A process for testing a program includes: receiving a variable comprising a plurality of input values; producing a plurality of equivalence classes for the input values; producing a representative value per equivalence class; producing, by a processor, a primary covering array comprising a plurality
Created October 9, 2019, Updated December 8, 2022