Comparison of SRGMs by using Adaboosting Algorithm » książka
Comparison of SRGMs by using Adaboosting Algorithm
ISBN-13: 9783659242021 / Angielski / Miękka / 2012 / 72 str.
Software Reliability is one of the important aspects of computer software which can be taken into consideration when determining the quality of the software. Building good reliability models is one of the key problems in the field of software reliability. A good software reliability model should give good predictions of future failure behavior, compute useful quantities and be widely applicable. Software Reliability Growth Models (SRGMs) are very important for estimating and predicting software reliability. An ideal SRGM should provide consistently accurate reliability estimation and prediction across different projects. However, that there is no single such model which can obtain accurate results for different cases. Thus, combining some individual SRGMs than single model is helpful to obtain more accurate estimation and prediction. Several combinational methods of SRGMs have been used to improve the reliability estimation and prediction accuracy.
Software Reliability is one of the important aspects of computer software which can be taken into consideration when determining the quality of the software. Building good reliability models is one of the key problems in the field of software reliability. A good software reliability model should give good predictions of future failure behavior, compute useful quantities and be widely applicable. Software Reliability Growth Models (SRGMs) are very important for estimating and predicting software reliability. An ideal SRGM should provide consistently accurate reliability estimation and prediction across different projects. However, that there is no single such model which can obtain accurate results for different cases. Thus, combining some individual SRGMs than single model is helpful to obtain more accurate estimation and prediction. Several combinational methods of SRGMs have been used to improve the reliability estimation and prediction accuracy.
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