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Decision Rule for Investment in Reusable Code

Decision Rule for Investment in Reusable Code

Roy Gelbard
Copyright: © 2009 |Pages: 7
ISBN13: 9781605663449|ISBN10: 1605663441|EISBN13: 9781605663456
DOI: 10.4018/978-1-60566-344-9.ch012
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MLA

Gelbard, Roy. "Decision Rule for Investment in Reusable Code." Systems Analysis and Design for Advanced Modeling Methods: Best Practices, edited by Akhilesh Bajaj and Stanislaw Wrycza, IGI Global, 2009, pp. 154-160. https://doi.org/10.4018/978-1-60566-344-9.ch012

APA

Gelbard, R. (2009). Decision Rule for Investment in Reusable Code. In A. Bajaj & S. Wrycza (Eds.), Systems Analysis and Design for Advanced Modeling Methods: Best Practices (pp. 154-160). IGI Global. https://doi.org/10.4018/978-1-60566-344-9.ch012

Chicago

Gelbard, Roy. "Decision Rule for Investment in Reusable Code." In Systems Analysis and Design for Advanced Modeling Methods: Best Practices, edited by Akhilesh Bajaj and Stanislaw Wrycza, 154-160. Hershey, PA: IGI Global, 2009. https://doi.org/10.4018/978-1-60566-344-9.ch012

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Abstract

Reusable code helps to decrease code errors, code units and therefore development time. It serves to improve quality and productivity frameworks in software development. The question is not HOW to make the code reusable, but WHICH amount of software components would be most beneficial (i.e. costeffective in terms of reuse), and WHAT method should be used to decide whether to make a component reusable or not. If we had unlimited time and resources, we could write any code unit in a reusable way. In other words, its reusability would be 100%. However, in real life, resources and time are limited. Given these constraints, decisions regarding reusability are not always straightforward. The current chapter focuses on decision-making rules for investing in reusable code. It attempts to determine the parameters, which should be taken into account in decisions relating to degrees of reusability. Two new models are presented for decisions-making relating to reusability: (i) a restricted model, and (ii) a non-restricted model. Decisions made by using these models are then analyzed and discussed.

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