Web software reliability modeling with random impulsive shocks

Abstract

As the web-server based business is rapidly developed and popularized, how to evaluate and improve the reliability of web-servers has been extremely important. Although a large number of software reliability growth models (SRGMs), including those combined with multiple change-points (CPs), have been available, these conventional SRGMs cannot be directly applied to web software reliability analysis because of the complex web operational profile. To characterize the web operational profile precisely, it should be realized that the workload of a web server is normally non-homogeneous and often observed with the pattern of random impulsive shocks. A web software reliability model with random impulsive shocks and its statistical analysis method are developed. In the proposed model, the web server workload is characterized by a geometric Brownian motion process. Based on a real data set from IIS server logs of ICRMS website (www.icrms.cn), the proposed model is demonstrated to be powerful for estimating impulsive shocks and web software reliability.

MuSRGM: A Genetic Algorithm-Based Dynamic Combinatorial Deep Learning Model for Software Reliability Engineering

“…After each iteration of the genetic algorithm, the next gen-eration of the population is generated. The offspring need to be evaluated using a fitness function [32], [33]. The fitness function assesses the proximity of an individual solution to the ideal solution [34], and we use Mean Squared Error (MSE) as the criterion for the fitness function.…”

A novel CRITIC‐TOPSIS approach for optimal selection of software reliability growth model (SRGM)

“…Huang and Lyu 20 incorporated the concept of multiple change points including points in time when there is change in software environment. Yang et al 21 developed a software reliability model of web considering random impulsive shocks and its statistical analysis method. In the proposed model the web server workload is characterized by a geometric Brownian motion process.…”

“…Yang et al 21 Considered random impulsive shocks and statistical analysis method to develop web software reliability model Li et el. 22 Proposed two S-shaped functions describing the growth trend Zhang et al 23 Incorporated rate of mutable fault detection and testing effort function Huang and Kuo 24 Analyzed fault removal process of system software Kumar et al 25 Proposed reliable growth model incorporating software patching Yaghoobi 26 Provided family of Gompertz distribution for fitting software failure times Anand et al 27 Studied the change in reliability due to multi-version software insertion of an infected patch Kumar and Sahni 28 Used optimal control theoretic method to estimate the optimal policy and genetic algorithm for estimating the test effort Liu and Zhao 29 Combined CRITIC and AHP approaches to assess the index weight Bansal et al 30 Designed fuzzy MCDM methods to select software effort estimation model Song and Peng 31 Proposed MCDM method for evaluation of imbalanced classifiers in bankruptcy and credit risk Youssef 32 Incorporated TOPSIS and BWM to rank CSPs Goswami and Mitra 33 Applied ARAS and COPRAS to determine the optimal mobile model from ten alternatives Dahooie et al 34 Used grey additive ratio assessment (ARAS-G) and stepwise weight assessment ratio analysis (SWARA) methods to choose best information technology (IT) Jocic et al 35 Proposed pivot pairwise relative criteria importance assessment (PIPRECIA) method and interval-valued triangular fuzzy additive ratio assessment (ARAS) for the selection of e-learning course Ghenai et al 36 Step-wise Weight Assessment Ratio Analysis/Additive Ratio Assessment (SWARA/ARAS) method for the assessment of sustainability indicators for renewable energy Zavadskas and Turskis 37 ARAS approach to assess microclimate in office rooms Kumar et al 38 Formulated Fuzzy data envelopment analysis (DEA) approach to rank SRGM Sharma et al 39 Developed distance based approach to rank SRGM Kumar et al 40 Developed MCDM based model using entropy and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS)…”

A case study on reliability and usability testing of a Web portal

“…The gap in the current studies is due to the fact that conventional software reliability models cannot be applied on web-based software due to the complexity of web operational profile [16] and also web software test coverage is unachieved by on Iy code coverage or execution parth coverage [12], [13], [14] besides it requires more focus on usability and its metrics. Thus this gap motivates our study as there is always a need to perform reliability testing with improved metrices and better coverage.…”