By P.K. Kapur, Hoang Pham, A. Gupta, P.C. Jha
Software Reliability evaluation with OR Applications is a complete consultant to software program reliability size, prediction, and regulate. It presents an intensive knowing of the sphere and provides strategies to the decision-making difficulties that difficulty software program builders, engineers, practitioners, scientists, and researchers. utilizing operations learn recommendations, readers will how to clear up difficulties below constraints comparable to price, funds and schedules to accomplish the top attainable caliber level.
Software Reliability review with OR Applications is a complete textual content on software program engineering and utilized data, state-of-the paintings software program reliability modeling, innovations and techniques for reliability evaluate, and comparable optimization difficulties. It addresses a variety of issues, including:
- unification methodologies in software program reliability overview;
- application of neural networks to software program reliability assessment;
- software reliability development modeling utilizing stochastic differential equations;
- software unencumber time and source allocation difficulties; and
- optimum part choice and reliability research for fault tolerant systems.
Software Reliability evaluation with OR Applications is designed to cater to the wishes of software program engineering practitioners, builders, safeguard or danger managers, and statisticians. it will probably even be used as a textbook for complex undergraduate or postgraduate classes in software program reliability, commercial engineering, and operations learn and administration.
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Extra resources for Software Reliability Assessment with OR Applications
First we carry out a comparison between the two, which enables us in building better understanding of software reliability modeling. 1 Let Us Compare: Software Versus Hardware Reliability Reliability measure applied either to software or hardware refers to the quality of the product and strives systematically to reduce or eliminate system failures. The major difference in the reliability analysis of the two systems is due to their failure mechanism [3, 5]. Failures in hardware is primarily due to material deterioration, aging, random failures, misuse, changes in environmental factors, design errors, etc.
In order to elaborate this point let us first define reliability. Statistically, reliability is defined as the ‘‘probability that software system will perform its function failure free under the specified environmental conditions and design limits for a specified period of time’’. This definition of reliability needs a careful understanding; first of all the statement that it will perform its function means the intended use of the software, defined in the specification and requirement documents.
Xn ; ðh1 ; h2 ; . ; hk ÞÞ ¼ k Y f ð X i ; hÞ i¼1 _ The likelihood estimator h can now be computed by maximizing L(X; h) with respect to h. In practice, it is often easier to maximize ln L(X; h) rather than L(X; h) due to easy of computations as compared to the actual likelihood function. The estimates of h = (h1, h2, …, hk) obtained maximizing ln L(X; h) maximize L(X; h) as logarithm function is monotonic. The log likelihood function is given by ln LðX; hÞ ¼ k X i¼1 ln f ðXi ; hÞ 38 1 Introduction In general the mechanics of obtaining MLE can be summarized as: (a) (b) (c) (d) (e) Find the joint density function L(X; h).
Software Reliability Assessment with OR Applications by P.K. Kapur, Hoang Pham, A. Gupta, P.C. Jha