STEM Workshop: Statistical TEst Methods Workshop
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Organization
General Chair: Manuel Barragan (TIMA, Grenoble, France)
Program Chair: Gildas Leger (Institute of Microelectronics of Seville, Seville, Spain)
Advance Program
You can download the advance program [here]
Call For Papers
Statistical test methods represent a promising step towards the reduction of the ever-increasing test costs for complex integrated systems. As opposed to traditional tests, based on extensive direct measurements, statistical test methods rely on building statistical models to infer the desired test information from simpler observables. Moreover, harvested statistical test data can be used to improve diagnosis and enable silicon-debug capabilities.
The introduction of advanced mathematical tools for statistical data processing offers a powerful set of tools for facing the test problem. Indeed, in the last years statistical processing has opened a number of novel and interesting research lines within the field of IC testing. Alternate test, statistical timing models, automatic test vector generation, statistical fault models, adaptive tests, statistical test compaction, process variation models at wafer level, yield modeling, aging/reliability modeling, etc, are just some examples of hot research topics directly based on statistical techniques.
The objective of this workshop is to provide an environment where researchers from academia and industry can discuss their latest findings, approaches, and ongoing work on all aspects of statistical test methods, from purely mathematical advancements to actual production test experiences.
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