Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

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Handbook of software reliability engineering

Computer Aided Civil and Infrastructure Engineering

https://cyberleninka.org/article/n/1407659.pdf

Lion Optimization Algorithm (LOA): A nature-inspired metaheuristic algorithm

Models in Ecology

Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is increasing popularity in resolving different optimization problems and has been widely utilized in various applications. In the past decades, numerous swarm intelligence algorithms have been developed, including ant colony optimization (ACO), particle swarm optimization (PSO), artificial fish swarm (AFS), bacterial foraging optimization (BFO), and artificial bee colony (ABC). This review tries to review the most representative swarm intelligence algorithms in chronological order by highlighting the functions and strengths from 127 research literatures. It provides an overview of the various swarm intelligence algorithms and their advanced developments, and briefly provides the description of their successful applications in optimization problems of engineering fields. Finally, opinions and perspectives on the trends and prospects in this relatively new research domain are represented to support future developments.

/pdf/a-review-on-representative-swarm-intelligence-algorithms-for-4f005x62n2.pdf

A Review on Representative Swarm Intelligence Algorithms for Solving Optimization Problems: Applications and Trends

This paper presents the solution of first order non-linear differential equation in fuzzy environment. Here, coefficients and initial condition are taken as the generalized trapezoidal fuzzy numbers of logistic fuzzy differential equation. The solution procedure of this non-linear fuzzy differential equation are developed with both linear and non-linear spread of fuzzy number. Numerical solutions are presented of the proposed solution procedure of logistic fuzzy differential equation.

G. S. Mahapatra

Papers

Fuzzy logistic differential equation with application using generalized trapezoidal fuzzy number