Agent-based unit testing environment for extreme programming.

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Title: Agent-based unit testing environment for extreme programming.
Authors: Yong-Feng Lin1, Ming-Wei Huang1, Chen, Jason Jen-Yen1 jychen@csie.ncu.edu.tw
Source: Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.). 2006 Supplement 1, Vol. 6 Issue 5, p1-8. 8p. 4 Diagrams.
Subjects: Extreme programming, MAS (Computer system), Computer programming, Software engineering, Java programming language
Abstract: This paper presents a new approach of using multi-agent system (MAS) to build a software engineering environment to support unit testing process for extreme programming (XP). The MAS reference model by Foundation for Intelligent Physical Agents (FIPA) is extended in this paper. The extended components are: 1) agent roles, 2) storage components, and 3) ontology. The FIPA-complied Java Agent Development framework (JADE) agent platform is used in implementation. The Darpa agent mark-up language (DAML) is used as process data format, including ontology. And, JENA API by Hewlett-Packard (HP) is used to store DAML ontology. Further, examples are given to show feasibility of this approach. The expected benefits of this agent-based approach are to: 1) Improve environment flexibility and reliability, 2) Facilitate XP practices, and 3) Use DAML format that is suitable for agents. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: Agent-based unit testing environment for extreme programming.
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  Data: <searchLink fieldCode="AR" term="%22Yong-Feng+Lin%22">Yong-Feng Lin</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Ming-Wei+Huang%22">Ming-Wei Huang</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Chen%2C+Jason+Jen-Yen%22">Chen, Jason Jen-Yen</searchLink><relatesTo>1</relatesTo><i> jychen@csie.ncu.edu.tw</i>
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  Data: <searchLink fieldCode="DE" term="%22Extreme+programming%22">Extreme programming</searchLink><br /><searchLink fieldCode="DE" term="%22MAS+%28Computer+system%29%22">MAS (Computer system)</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+programming%22">Computer programming</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Java+programming+language%22">Java programming language</searchLink>
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  Data: This paper presents a new approach of using multi-agent system (MAS) to build a software engineering environment to support unit testing process for extreme programming (XP). The MAS reference model by Foundation for Intelligent Physical Agents (FIPA) is extended in this paper. The extended components are: 1) agent roles, 2) storage components, and 3) ontology. The FIPA-complied Java Agent Development framework (JADE) agent platform is used in implementation. The Darpa agent mark-up language (DAML) is used as process data format, including ontology. And, JENA API by Hewlett-Packard (HP) is used to store DAML ontology. Further, examples are given to show feasibility of this approach. The expected benefits of this agent-based approach are to: 1) Improve environment flexibility and reliability, 2) Facilitate XP practices, and 3) Use DAML format that is suitable for agents. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Computational Methods in Sciences & Engineering (Sage Publications Inc.) is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3233/jcm-2006-6s101
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        Text: English
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        Type: general
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              Text: 2006 Supplement 1
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              Y: 2006
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