In search of the optimum test set - adaptive test methods for maximum defect coverage and lowest test cost

Author(s):  
R. Madge ◽  
B. Benware ◽  
R. Turakhia ◽  
R. Daasch ◽  
C. Schuermyer ◽  
...  
Electronics ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 680
Author(s):  
Huaguo Liang ◽  
Jinlei Wan ◽  
Tai Song ◽  
Wangchao Hou

With the growing complexity of integrated circuits (ICs), more and more test items are required in testing. However, the large number of invalid items (which narrowly pass the test) continues to increase the test time and, consequently, test costs. Aiming to address the problems of long test time and reduced test item efficiency, this paper presents a method which combines a fast correlation-based filter (FCBF) and a weighted naive Bayesian model which can identify the most effective items and make accurate quality predictions. Experimental results demonstrate that the proposed method reduces test time by around 2.59% and leads to fewer test escapes compared with the recently adopted test methods. The study shows that the proposed method can effectively reduce the test cost without jeopardizing test quality excessively.


2014 ◽  
Vol 529 ◽  
pp. 359-363
Author(s):  
Xi Lei Huang ◽  
Mao Xiang Yi ◽  
Lin Wang ◽  
Hua Guo Liang

A novel concurrent core test approach is proposed to reduce the test cost of SoC. Before test, a novel test set sharing strategy is proposed to obtain a minimum size of merged test set by merging the test sets corresponding to cores under test (CUT).Moreover, it can be used in conjunction with general compression/decompression techniques to further reduce test data volume (TDV). During test, the proposed vector separating device which is composed of a set of simple combinational logical circuit (CLC) is designed for separating the vector from the merged test set to the correspondent test core. This approach does not add any test vector for each core and can test synchronously to reduce test application time (TAT). Experimental results for ISCAS’ 89 benchmarks have been rproven the efficiency of the proposed approach.


2009 ◽  
Vol 2009 (1) ◽  
pp. 191-193
Author(s):  
Sebastian Szałkowski ◽  
Marcin Gębski

Static and Fatigue Structural Tests for EADS-CASA The paper presents structural tests of Airbus aircraft subcomponents which have been carried out at the Institute of Aviation in Warsaw to the order of EADS CASA in Madrid since 2004. Subcomponents of A318 and A400M aircraft were tested. Short descriptions of tested specimens, test set-up and test methods are included.


2021 ◽  
Author(s):  
Houjun Liu

In this experiment, a model was devised, trained, and evaluated to automate psychotherapist/client text conversations through state-of-the-art, Seq2Seq Transformer-based Natural Language Generation (NLG) systems. Through training upon a mix of the Cornell Movie Dialogue Corpus for language understanding and an open-source, anonymized, and public licensed psychotherapeutic dataset, the model achieved statistically significant performance in published, standardized qualitative benchmarks against human validation data — meeting or exceeding human-written response performance in 59.7% and 67.1% of the test set two independent test methods respectively. Although the model cannot replace the work of psychotherapy, its ability to synthesize human-appearing utterances for the majority of the test set serves as a promising step towards communizing and easing tensions at the psychotherapeutic point-of-care.


2013 ◽  
Vol 321-324 ◽  
pp. 697-702 ◽  
Author(s):  
Guo Jian Huang ◽  
Dong Hui Wang ◽  
Xin Hua Wang ◽  
Wei Wei Wang

The choice of the number and location of sensors in the structure is the foundation of cranes structural health monitoring, which has major influence on the monitoring results. This paper taking a gantry crane as a SHM research object, uses optimal sensor placement based on Finite Element Method, the stress concentration points could be drawn by the FEM calculation results. This method carry out dynamic load stress analysis for the structure with virtual prototype, which make up for the lack of static analysis; compared with the type test methods, not only reduce the test cost, but also more flexible, and break through the restrictions of all types of extreme conditions. This method makes the sensor data obtained more realistically reflects the crane structure condition; provides reliable data support for crane safety monitoring and safety evaluation. The promotion of this method will provide important technical support for the development of the crane SHM.


2018 ◽  
Vol 35 (13) ◽  
pp. 2251-2257 ◽  
Author(s):  
Bin Guo ◽  
Baolin Wu

Abstract Motivation Genetics hold great promise to precision medicine by tailoring treatment to the individual patient based on their genetic profiles. Toward this goal, many large-scale genome-wide association studies (GWAS) have been performed in the last decade to identify genetic variants associated with various traits and diseases. They have successfully identified tens of thousands of disease-related variants. However they have explained only a small proportion of the overall trait heritability for most traits and are of very limited clinical use. This is partly owing to the small effect sizes of most genetic variants, and the common practice of testing association between one trait and one genetic variant at a time in most GWAS, even when multiple related traits are often measured for each individual. Increasing evidence suggests that many genetic variants can influence multiple traits simultaneously, and we can gain more power by testing association of multiple traits simultaneously. It is appealing to develop novel multi-trait association test methods that need only GWAS summary data, since it is generally very hard to access the individual-level GWAS phenotype and genotype data. Results Many existing GWAS summary data-based association test methods have relied on ad hoc approach or crude Monte Carlo approximation. In this article, we develop rigorous statistical methods for efficient and powerful multi-trait association test. We develop robust and efficient methods to accurately estimate the marginal trait correlation matrix using only GWAS summary data. We construct the principal component (PC)-based association test from the summary statistics. PC-based test has optimal power when the underlying multi-trait signal can be captured by the first PC, and otherwise it will have suboptimal performance. We develop an adaptive test by optimally weighting the PC-based test and the omnibus chi-square test to achieve robust performance under various scenarios. We develop efficient numerical algorithms to compute the analytical P-values for all the proposed tests without the need of Monte Carlo sampling. We illustrate the utility of proposed methods through application to the GWAS meta-analysis summary data for multiple lipids and glycemic traits. We identify multiple novel loci that were missed by individual trait-based association test. Availability and implementation All the proposed methods are implemented in an R package available at http://www.github.com/baolinwu/MTAR. The developed R programs are extremely efficient: it takes less than 2 min to compute the list of genome-wide significant single nucleotide polymorphisms (SNPs) for all proposed multi-trait tests for the lipids GWAS summary data with 2.5 million SNPs on a single Linux desktop. Supplementary information Supplementary data are available at Bioinformatics online.


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