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Statistical testing based on a Markov chain usage model, as a rigorous testing method, has been around for more than two decades. Through the comprehensive application of statistical science to the testing of software, it provides audit trails of evidence to support correctness arguments for a software-intensive system as well as a decision that the system is of requisite quality for its intended...
In this paper, a novel hardware-oriented local dimming content adaptive backlight control (CABC) algorithm is proposed for liquid crystal displays (LCDs). It utilizes an efficient backlight dimming algorithm to reduce the power consumption of the backlight module in LCD and uses a contrast compensation algorithm to compensate the brightness distortion. In order to dim the backlight power and compensate...
Markov chain usage-based statistical testing has been an effective means in the economical production of high quality software that also provides credible evidence to support its dependability. Sequence-based specification is a rigorous specification method that derives a formal system model from informal functional requirements, which can be used as a formal method to construct a Markov chain usage...
Markov chain usage models have been a basis for statistical testing of software intensive systems for more than two decades. During this time, several reliability estimators have been formulated and used in testing. This paper presents an improvement on the arc-based Bayesian estimator distributed with Version 4.5 of the JUMBL (J Usage Model Builder Library) [1]. The arc-based Bayesian estimator is...
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