Data quality assessment in product failure prediction models

Operationalised product quality models and assessment: The Quamoco approach

Context: Software quality models provide either abstract quality characteristics or concrete quality measurements; there is no seamless integration of these two aspects. Quality assessment approaches are, hence, also very specific or remain abstract. Reasons for this include the complexity of quality and the various quality profiles in different domains which make it difficult to build operatio...

Monitoring Data Product Quality

Prediction and quality assessment of transposon insertion display data.

Vol. 36, No. 2 (2004) BioTechniques 223 Transposons are mobile sequences commonly found in prokaryotic and eukaryotic genomes. Their dispersal, repetitiveness, and the fact that their mobilization is a source of polymorphism make them choice candidates for use as molecular markers in mapping technologies. In recent years, variations of a technique inspired by amplified fragment length polymorph...

Assessment of survival prediction models based on microarray data

MOTIVATION In the process of developing risk prediction models, various steps of model building and model selection are involved. If this process is not adequately controlled, overfitting may result in serious overoptimism leading to potentially erroneous conclusions. METHODS For right censored time-to-event data, we estimate the prediction error for assessing the performance of a risk predic...

Defect Prediction Leads to High Quality Product

Defect prediction is relatively a new research area of software quality assurance. A project team always aims to produce a quality product with zero or few defects. Quality of a product is correlated with the number of defects as well as it is limited by time and by money. So, defect prediction is very important in the field of software quality and software reliability. This paper gives you a v...