A Statistical Theory of Digital Circuit Testability
IEEE Transactions on Computers
An Examination of Fault Exposure Ratio
IEEE Transactions on Software Engineering - Special issue on software reliability
Arithmetic Additive Generators of Pseudo-Exhaustive Test Patterns
IEEE Transactions on Computers
Transparent random access memory testing for pattern sensitive faults
Journal of Electronic Testing: Theory and Applications
Exhaustive and Near-Exhaustive Memory Testing Techniques and theirBIST Implementations
Journal of Electronic Testing: Theory and Applications
Fast Antirandom (FAR) Test Generation
HASE '98 The 3rd IEEE International Symposium on High-Assurance Systems Engineering
ATS '02 Proceedings of the 11th Asian Test Symposium
An Empirical Analysis of Equivalence Partitioning, Boundary Value Analysis and Random Testing
METRICS '97 Proceedings of the 4th International Symposium on Software Metrics
Antirandom vs. Psuedorandom Testing
ICCD '98 Proceedings of the International Conference on Computer Design
Experimental Evaluation of Pseudorandom Test Effectiveness
EUROMICRO '98 Proceedings of the 24th Conference on EUROMICRO - Volume 1
.NET Test Automation Recipes: A Problem-Solution Approach
.NET Test Automation Recipes: A Problem-Solution Approach
Object distance and its application to adaptive random testing of object-oriented programs
Proceedings of the 1st international workshop on Random testing
Pseudo-Exhaustive Testing for Software
SEW '06 Proceedings of the 30th Annual IEEE/NASA Software Engineering Workshop
Exhaustive Generation of Bit Patterns with Applications to VLSI Self-Testing
IEEE Transactions on Computers
Exhaustive Test Pattern Generation with Constant Weight Vectors
IEEE Transactions on Computers
Antirandom testing: a distance-based approach
VLSI Design
Orderly Random Testing for Both Hardware and Software
PRDC '08 Proceedings of the 2008 14th IEEE Pacific Rim International Symposium on Dependable Computing
Optimal Backgrounds Selection for Multi Run Memory Testing
DDECS '08 Proceedings of the 2008 11th IEEE Workshop on Design and Diagnostics of Electronic Circuits and Systems
Adaptive Random Testing: The ART of test case diversity
Journal of Systems and Software
Adaptive Random Testing by Exclusion through Test Profile
QSIC '10 Proceedings of the 2010 10th International Conference on Quality Software
Using Coverage Information to Guide Test Case Selection in Adaptive Random Testing
COMPSACW '10 Proceedings of the 2010 IEEE 34th Annual Computer Software and Applications Conference Workshops
The coverage problem for random testing
ITC'84 Proceedings of the 1984 international test conference on The three faces of test: design, characterization, production
Analysis of multibackground memory testing techniques
International Journal of Applied Mathematics and Computer Science - Computational Intelligence in Modern Control Systems
ASIAN'04 Proceedings of the 9th Asian Computing Science conference on Advances in Computer Science: dedicated to Jean-Louis Lassez on the Occasion of His 5th Cycle Birthday
An Evaluation of Random Testing
IEEE Transactions on Software Engineering
Circuits for pseudoexhaustive test pattern generation
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Hi-index | 0.00 |
Antirandom testing has proved useful in a series of empricial evaluations. It improves the fault-detection capability of random testing by employing the location information of previously executed test cases. In antirandom testing we select test pattern (test vector) such that it is as different as possible from all the previous executed test cases. Unfortunately, this method essentially requires enumeration of the input space and computation of each input vector when used on an arbitrary set of existing test data. This avoids scale-up to large test sets and (or) long input vectors. In this paper, we propose a new algorithm for antirandom test generation that is computationally feasible for BIST (Built In Self Test) tests. As the fitness function we use Maximal Minimal Hamming Distance (MMHD) rather than standard Hamming distance as is used in the classical approach. This allows to generate the most efficient test vectors in term of weighted number of generated k-bits tuples. Experimental results are given to evaluate the performance of the new approach.