过分爱国主义
发表于 2025-3-21 19:17:09
书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0620613<br><br> <br><br>书目名称Machine Learning for Dynamic Software Analysis: Potentials and Limits读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0620613<br><br> <br><br>
口音在加重
发表于 2025-3-21 20:17:32
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COMMA
发表于 2025-3-22 03:18:31
Amel Bennaceur,Reiner Hähnle,Karl MeinkeWritten by international experts.Presents the state of the art and suggests new directions and collaborations for future research.Gives an overview of the machine learning techniques that can be used
沉思的鱼
发表于 2025-3-22 04:38:43
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Inscrutable
发表于 2025-3-22 08:47:45
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软弱
发表于 2025-3-22 14:59:02
Machine Learning for Dynamic Software Analysis: Potentials and Limits978-3-319-96562-8Series ISSN 0302-9743 Series E-ISSN 1611-3349
Arctic
发表于 2025-3-22 20:27:03
Learning-Based Testing: Recent Progress and Future Prospectsrics enable a precise, general and quantitative approach to both speed of learning and test coverage. Moreover, quantitative approaches to black-box test coverage serve to distinguish LBT from alternative approaches such as random and search-based testing. We conclude by outlining some prospects for future research.
Affirm
发表于 2025-3-23 00:25:40
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蹒跚
发表于 2025-3-23 04:41:41
Constraint-Based Behavioral Consistency of Evolving Software Systemsnd we describe some of the research challenges that must be solved. Our main idea is to combine software analysis approaches represented by various forms of static analysis and formal verification with runtime verification, monitoring, and automata learning in order to optimally leverage the de facto observed behaviour of the deployed systems.
guardianship
发表于 2025-3-23 06:23:14
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