Testing and Validating Machine Learning Classifiers by Metamorphic Testing.

Machine Learning algorithms have provided core functionality to many application domains - such as bioinformatics, computational linguistics, etc. However, it is difficult to detect faults in such applications because often there is no "test oracle" to verify the correctness of the computed outputs. To help address the software quality, in this paper we present a technique for testing the implementations of machine learning classification algorithms which support such applications.

Application of Metamorphic Testing to Supervised Classifiers.

Many applications in the field of scientific computing - such as computational biology, computational linguistics, and others - depend on Machine Learning algorithms to provide important core functionality to support solutions in the particular problem domains. However, it is difficult to test such applications because often there is no "test oracle" to indicate what the correct output should be for arbitrary input. To help address the quality of such software, in this paper we present a technique for testing the implementations of supervised machine learning classification algorithms on which such scientific computing software depends.

Automatic Detection of Previously-Unseen Application States for Deployment Environment Testing and Analysis.

For large, complex software systems, it is typically impossible in terms of time and cost to reliably test the application in all possible execution states and configurations before releasing it into production. One proposed way of addressing this problem has been to continue testing and analysis of the application in the field, after it has been deployed. A practical limitation of many such automated approaches is the potentially high performance overhead incurred by the necessary instrumentation.

CONFU: Configuration Fuzzing Testing Framework for Software Vulnerability Detection.

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations and inputs together with a certain runtime environment.

Configuration Fuzzing for Software Vulnerability Detection.

Many software security vulnerabilities only reveal themselves under certain conditions, i.e., particular configurations of the software together with its particular runtime environment.

weHelp: A Reference Architecture for Social Recommender Systems.

Recommender systems have become increasingly popular. Most of the research on recommender systems has focused on recommendation algorithms. There has been relatively little research, however, in the area of generalized system architectures for recommendation systems.

Reduction of tumor necrosis factor induced nuclear factor-kappaB nuclear translocation and DNA binding by dexamethasone in human osteoarthritic synovial tissue explants.

Objective: The antiinflammatory effects of glucocorticoids are mediated by several mechanisms, including inhibition of nuclear factor-kappaB (NF-kappaB) nuclear translocation and DNA binding. This mechanism is not evident in some cell types, including endothelial cells and rheumatoid arthritis (RA) fibroblast-like synoviocytes (FLS). We determined the effect of glucocorticoids and tumor necrosis factor (TNF) on nuclear localization and DNA binding of the transcription factor NF-kappaB in osteoarthritic (OA) synovial tissue.