The Impact of Details in the Class Diagram on Software Size Estimation.

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Title: The Impact of Details in the Class Diagram on Software Size Estimation.
Authors: Živkovič, Aleš1 ales.zivkovic@uni-mb.si, Heričko, Marjan1, Brumen, Boštjan1, Beloglavec, Simon1, Rozman, Ivan1
Source: Informatica. 2005, Vol. 16 Issue 2, p295-312. 18p.
Subjects: Computer software, Function point analysis, Software engineering, Software productivity, Software measurement, Computer systems
Abstract: Software size is an important attribute in software project planning. Several methods for software size estimation are available; most of them are based on function points. Albrecht introduced function points as a technologically independent method with its own software abstraction layer. However, it is difficult to apply original abstraction elements to current technologies. Therefore researchers introduced additional rules and mappings for object‐based solutions. In this paper several mapping strategies are discussed and compared. Based on the similarities in compared mappings, a common mapping strategy is then defined. This mapping is then tested on the reference application portfolio containing five applications. The aim of the test scenario is to evaluate the impact of the diverse detail levels in the class diagrams on software size measurement. Although the question of how to perform quality size measurements in object‐oriented projects remains unanswered, the paper gives valuable information on the topic, supported by mathematics. [ABSTRACT FROM AUTHOR]
Copyright of Informatica is the property of Vilnius University, Institute of Data Science & Digital Technologies 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.)
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  Data: <searchLink fieldCode="DE" term="%22Computer+software%22">Computer software</searchLink><br /><searchLink fieldCode="DE" term="%22Function+point+analysis%22">Function point analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Software+engineering%22">Software engineering</searchLink><br /><searchLink fieldCode="DE" term="%22Software+productivity%22">Software productivity</searchLink><br /><searchLink fieldCode="DE" term="%22Software+measurement%22">Software measurement</searchLink><br /><searchLink fieldCode="DE" term="%22Computer+systems%22">Computer systems</searchLink>
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  Data: Software size is an important attribute in software project planning. Several methods for software size estimation are available; most of them are based on function points. Albrecht introduced function points as a technologically independent method with its own software abstraction layer. However, it is difficult to apply original abstraction elements to current technologies. Therefore researchers introduced additional rules and mappings for object‐based solutions. In this paper several mapping strategies are discussed and compared. Based on the similarities in compared mappings, a common mapping strategy is then defined. This mapping is then tested on the reference application portfolio containing five applications. The aim of the test scenario is to evaluate the impact of the diverse detail levels in the class diagrams on software size measurement. Although the question of how to perform quality size measurements in object‐oriented projects remains unanswered, the paper gives valuable information on the topic, supported by mathematics. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Informatica is the property of Vilnius University, Institute of Data Science & Digital Technologies 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: 10.15388/informatica.2005.100
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        Text: English
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