<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>Applied OSS Reliability Assessment Modeling, AI and Tools</title>
    <subTitle>Mathematics and AI for OSS Reliability Assessment</subTitle>
  </titleInfo>
  <name type="personal">
    <namePart>Tamura, Yoshinobu.</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">aut</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/aut</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Yamada, Shigeru.</namePart>
    <role>
      <roleTerm type="text">author.</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">aut</roleTerm>
    </role>
    <role>
      <roleTerm authority="marcrelator" type="code">http://id.loc.gov/vocabulary/relators/aut</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>SpringerLink (Online service)</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">sz</placeTerm>
    </place>
    <dateIssued encoding="marc">2024</dateIssued>
    <edition>1st ed. 2024.</edition>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">electronic</form>
    <form authority="gmd">electronic resource</form>
    <reformattingQuality>access</reformattingQuality>
    <extent>XI, 188 p. 99 illus., 80 illus. in color. online resource.</extent>
  </physicalDescription>
  <abstract>This textbook introduces the theory and application of open source software (OSS) reliability. The measurement and management of open source software are essential to produce and maintain quality and reliable systems while using open source software. This book describes the latest methods for the reliability assessment of open source software. It presents the state of the art of open source software reliability measurement and assessment based on stochastic modeling and deep learning approaches. It introduces several stochastic reliability analyses of OSS computing with application along with actual OSS project data. The book contains exercises to aid learning and is useful for graduate students and researchers.</abstract>
  <tableOfContents>Open Source Software Reliability -- Stochastic Differential Equation Model for OSS Reliability Analysis -- Dimensional Stochastic Differential Equation Model for OSS Reliability Analysis -- Jump Diffusion Process Model for OSS Reliability Analysis -- Cyclically Two Dimensional Stochastic Differential Equation Modeling -- Cyclically Two Dimensional Jump Diffusion Process Modeling -- Three Dimensional Tool Based on Noisy Model -- Deep Learning Method Based on fault big data Analysis for OSS Reliability Assessment -- Deep Learning Approach for OSS Reliability Assessment Considering Wiener Process -- Deep Learning Approach for OSS Reliability Assessment Considering Jump Diffusion Process -- Performance Illustrations of the Developed Application Tool Based on Deep Learning -- Exercise.</tableOfContents>
  <note type="statement of responsibility">by Yoshinobu Tamura, Shigeru Yamada.</note>
  <subject authority="lcsh">
    <topic>Open source software</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Artificial intelligence</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Cooperating objects (Computer systems)</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Industrial engineering</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Production engineering</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Data protection</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Computers</topic>
  </subject>
  <subject>
    <topic>Open Source</topic>
  </subject>
  <subject>
    <topic>Artificial Intelligence</topic>
  </subject>
  <subject>
    <topic>Cyber-Physical Systems</topic>
  </subject>
  <subject>
    <topic>Industrial and Production Engineering</topic>
  </subject>
  <subject>
    <topic>Data and Information Security</topic>
  </subject>
  <subject>
    <topic>Hardware Performance and Reliability</topic>
  </subject>
  <classification authority="lcc">QA76.76.O62</classification>
  <relatedItem type="host">
    <titleInfo>
      <title>Springer Nature eBook</title>
    </titleInfo>
  </relatedItem>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="otherFormat" displayLabel="Printed edition:"/>
  <relatedItem type="series">
    <titleInfo>
      <title>Springer Series in Reliability Engineering</title>
    </titleInfo>
  </relatedItem>
  <identifier type="isbn">9783031648038</identifier>
  <identifier type="uri">https://doi.org/10.1007/978-3-031-64803-8</identifier>
  <location>
    <url>https://doi.org/10.1007/978-3-031-64803-8</url>
  </location>
  <recordInfo>
    <recordCreationDate encoding="marc">240925</recordCreationDate>
    <recordChangeDate encoding="iso8601">20251030113103.0</recordChangeDate>
    <recordIdentifier source="DE-He213">978-3-031-64803-8</recordIdentifier>
  </recordInfo>
</mods>
