Abstract

The successful experience of adopting distributed development models in such open source projects includes GNU/Linux operating system, Apache HTTP server, Android, BusyBox, and so on. The open source project contains special features so-called software composition by which several geographically-dispersed compo-nents are developed in all parts of the world. We propose a method of component-oriented reliability as-sessment based on hierarchical Bayesian model and Markov chain Monte Carlo methods. Especially, we fo-cus on the fault-detection rate for each component reported to the bug tracking system. We can assess the reliability for the whole open source software system by using the confidence interval for each component. Also, we analyze actual software fault-count data to show numerical examples of reliability assessment for OSS.

Highlights

  • Software development environment has changed into new development paradigms such as concurrent distributed development environment and the so-called open source project by using network computing technologies [1]

  • We propose a method of component-oriented reliability assessment based on hierarchical Bayesian model and Markov chain Monte Carlo methods

  • We focus on the data of all platform for Apache HTTP Server 2 version

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Summary

Introduction

Software development environment has changed into new development paradigms such as concurrent distributed development environment and the so-called open source project by using network computing technologies [1]. Many software reliability growth models (SRGM’s) [3] have been applied to assess the reliability for quality management and testing-progress control of software development. The effective method of dynamic testing management for a new distributed development paradigm as typified by the open source project has only a few presented [4,5,6,7,8]. OSS is composed of several software components as a feature of distributed development environment In such cases, it is appropriate to apply the method of component based reliability assessment rather than one of reliability assessment based on SRGM’s.

Estimation of Predicted Distribution Based on Bayesian Theory
Hierarchical Bayesian Model
Numerical Examples
The Estimation Results Based on MCMC
D D t 1 t
Concluding Remarks
Full Text
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