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Search Publications by: Raghu N Kacker (Fed)

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Displaying 101 - 125 of 187

Efficient Algorithms for T-way Test Sequence Generation

October 16, 2012
Author(s)
Linbin Yu, Yu Lei, Raghu N. Kacker, D. Richard Kuhn, James F. Lawrence
Combinatorial testing has been shown to be a very effective testing strategy. Most work on combinatorial testing focuses on t-way test data generation, where each test is an unordered set of parameter values. In this paper, we study the problem of t-way

Measuring Combinatorial Coverage of System State-space for IV&V

September 13, 2012
Author(s)
David R. Kuhn, Raghu N. Kacker
This report describes some measures of combinatorial coverage that can be helpful in estimating this risk that we have applied to tests for spacecraft software but have general application to any combinatorial coverage problem. This method will be

Efficient Methods for Interoperability Testing Using Event Sequences

July 31, 2012
Author(s)
David R. Kuhn, James M. Higdon, J .M. Lawrence, Raghu N. Kacker, Yu Lei
Many software testing problems involve sequences of events. The methods described in this paper were motivated by testing needs of mission critical systems that may accept multiple communication or sensor inputs and generate output to several communication

A New Measure in Cell Image Segmentation Data Analysis

July 24, 2012
Author(s)
Jin Chu Wu, Michael W. Halter, Raghu N. Kacker, John T. Elliott
Cell image segmentation (CIS) is critical for quantitative imaging in cytometric analyses. The data derived after segmentation can be used to infer cellular function. To evaluate CIS algorithms, first for dealing with comparisons of single cells treated as

Data Dependency on Measurement Uncertainties in Speaker Recognition Evaluation

July 11, 2012
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The National Institute of Standards and Technology conducts an ongoing series of Speaker Recognition Evaluations (SRE). Speaker detection performance is measured using a detection cost function defined as a weighted sum of the probabilities of type I and

Combinatorial Testing

June 25, 2012
Author(s)
David R. Kuhn, Raghu N. Kacker, Yu Lei
Combinatorial testing is a method that can reduce cost and improve test effectiveness significantly for many applications. The key insight underlying this form of testing is that not every parameter contributes to every failure, and empirical data suggest

Combinatorial Methods for Event Sequence Testing

April 21, 2012
Author(s)
D. Richard Kuhn, James M. Higdon, James F. Lawrence, Raghu N. Kacker, Yu Lei
Many software testing problems involve sequences. This paper presents an application of combinatorial methods to testing problems for which it is important to test multiple configurations, but also to test the order in which events occur. For example, the

Combinatorial Testing of ACTS: A Case Study

April 21, 2012
Author(s)
Mehra N. Borazjany, Linbin Yu, Yu Lei, Raghu N. Kacker, D. Richard Kuhn
In this paper we present a case study of applying combinatorial testing to test a combinatorial test generation tool called ACTS. The purpose of this study is two-fold. First, we want to gain experience and insights about how to apply combinatorial testing

Combining Results from Multiple Evaluations of the Same Measurand

December 1, 2011
Author(s)
Raghu N. Kacker, Klaus-Dieter Sommer
According to the Guide to the Expression of Uncertainty in Measurement (GUM), a result of measurement consists of a measured value together with its associated standard uncertainty. The measured value and the standard uncertainty are interpreted as the

Uncertainties of Measures in Speaker Recognition Evaluation

November 10, 2011
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The National Institute of Standards and Technology (NIST) Speaker Recognition Evaluations (SRE) are an ongoing series of projects conducted by NIST. In the NIST SRE, speaker detection performance is measured using a detection cost function, which is

Data Dependency on Measurement Uncertainties in Speaker Recognition Evaluation

November 3, 2011
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The National Institute of Standards and Technology (NIST) has been conducting an ongoing series of Speaker Recognition Evaluations (SRE). Speaker detection performance is measured using a detection cost function defined as a weighted sum of the

A Combinatorial Approach to Detecting Buffer Overflow Vulnerabilities

June 14, 2011
Author(s)
Raghu N. Kacker, Yu Lei, David R. Kuhn, Wenhua Wang
Buffer overflow vulnerabilities are program defects that can cause a buffer overflow to occur at runtime. Many security attacks exploit buffer overflow vulnerabilities to compromise critical data structures. In this paper, we present a black-box testing

A Survey of Binary Covering Arrays

April 7, 2011
Author(s)
James F. Lawrence, Raghu N. Kacker, Yu Lei, David R. Kuhn, Michael Forbes
Two-valued covering arrays of strength t are 0--1 matrices having the property that for each t columns and each of the possible 2t sequences of t 0's and 1's, there exists a row having that sequence in that set of t columns. Covering arrays are an

Measures, Uncertainties, and Significance Test in Operational ROC Analysis

January 31, 2011
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
In operational ROC (receiver operating characteristic) analysis of fingerprint-image matching algorithms on large datasets, the measures and their accuracies are investigated in the three scenarios: 1) the true accept rate (TAR) of genuine scores at a

Derivation of Isosceles Trapezoidal Distribution

December 1, 2010
Author(s)
Raghu N. Kacker, James F. Lawrence
It is known that, if the mid-point of a rectangular distribution is specified, the half-width is inexactly known, and the state of knowledge about the half-width may be represented by a narrower rectangular distribution then the resulting distribution

Further Studies of Bootstrap Variability for ROC Analysis on Large Datasets

October 11, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
The nonparametric two-sample bootstrap is successfully applied to computing the measurement uncertainties in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition system, etc. To determine the

Validation of Two-Sample Bootstrap in ROC Analysis on Large Datasets Using AURC

October 11, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Raghu N. Kacker
Sampling variability can result in uncertainties of measures. The nonparametric two-sample bootstrap method has been used to compute uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets, such as the standard error

Practical Combinatorial Testing

October 7, 2010
Author(s)
David R. Kuhn, Raghu N. Kacker, Yu Lei
Combinatorial testing can help detect problems like this early in the testing life cycle. The key insight underlying t-way combinatorial testing is that not every parameter contributes to every fault and most faults are caused by interactions between a

Measurement Uncertainties in Speaker Recognition Evaluation

September 15, 2010
Author(s)
Jin Chu Wu, Alvin F. Martin, Craig S. Greenberg, Raghu N. Kacker
The speaker recognition evaluation is an ongoing series of evaluations conducted by NIST. A detection cost function is computed over the sequence of trials provided and used for all speaker detection tests while measuring speaker detection performance. The