International Journal of Software Engineering, Technology and Applications
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International Journal of Software Engineering, Technology and Applications (2 papers in press)
An Efficient Rejuvenation Policy to Cope with Software Aging Phenomenon by Amir Akhavan Bitaraf, Moona Yakhchi, Hakem Beitollahi, Mahdi Fazeli Abstract: Software aging is a well-known challenge in most software systems that lead
to serious performance degradation or frequent failures in these systems. Several
proactive rejuvenation techniques have been proposed to tackle software aging
and prevent failures. Rejuvenation techniques are mostly categorized into two
main classes: Time-based techniques and failure prediction based techniques.
This article proposes a new method for software rejuvenation that follows a
new policy for determining the time of rejuvenation. Our new policy includes two
parts: 1) Considering a set of rejuvenation time points based on a static analysis
of system behavior in the presence of software aging effect; 2) Dynamically
changing the scheduling points based on a dynamic analysis of system workload.
In fact, our policy employs a straightforward time-based technique as a base-line
and then dynamically changes the selected points based on predicting the lowest
workload time. In comparison to the second category of rejuvenation techniques, our
policy predicts the occurrence time of the lowest workload instead of occurrence
of failure time.
Our new strategy effectively and dynamically changes the static points of a
time-based policy. Simulation results in comparison to other well-known time-based
rejuvenation techniques indicate the system availability improves between 0.3%
to 7.3%. Moreover, our technique significantly reduces the overall rejuvenation
cost (up to 71%). Keywords: Software Aging; Software Rejuvenation.
A Robust Software Reliability Growth Model for Accurate Detection of Software Failures by Jagadeesh Medapati, Anand Chandulal Jasti, Rajinikanth TV Abstract: This paper pinpoints to detect and eliminate the actual software failures efficiently. The approach fits in a particular case of Generalized Gamma Mixture Model (GGMM), namely exponential distribution. The approach estimates two parameters using the Maximum Likelihood Estimate (MLE). Standard Evaluation metrics like Mean Square Error (MSE), Coefficient of Determination (R2), Sum of Squares (SSE), and Root Means Square Error (RMSE) were calculated. For the justification of the model selection and goodness of fit various model selection frameworks like Chi-Square Goodness of Fit, Walds Test, Akaike Information Criteria (AIC), AICc and Schwarz criterion (SBC) were also estimated. The experimentation was carried out on five benchmark datasets which interpret the considered novel technique identifies the actual failures on par with the existing models. This paper presents a robust software reliability growth model which is more effectual in the identification of the failures. This helps the present software organizations in the release of bug-free software just in time. Keywords: Software Reliability; Error; Reviews; Generalized Gamma Mixture Model; Benchmark Datasets.