Reference Hub7
Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms: Refactoring Prospective

Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms: Refactoring Prospective

Rasmita Panigrahi, Neelamdhab Padhy, Suresh Chandra Satapathy
Copyright: © 2019 |Volume: 10 |Issue: 2 |Pages: 16
ISSN: 1942-3926|EISSN: 1942-3934|EISBN13: 9781522565536|DOI: 10.4018/IJOSSP.2019040102
Cite Article Cite Article

MLA

Panigrahi, Rasmita, et al. "Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms: Refactoring Prospective." IJOSSP vol.10, no.2 2019: pp.21-36. http://doi.org/10.4018/IJOSSP.2019040102

APA

Panigrahi, R., Padhy, N., & Satapathy, S. C. (2019). Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms: Refactoring Prospective. International Journal of Open Source Software and Processes (IJOSSP), 10(2), 21-36. http://doi.org/10.4018/IJOSSP.2019040102

Chicago

Panigrahi, Rasmita, Neelamdhab Padhy, and Suresh Chandra Satapathy. "Software Reusability Metrics Estimation From the Social Media by Using Evolutionary Algorithms: Refactoring Prospective," International Journal of Open Source Software and Processes (IJOSSP) 10, no.2: 21-36. http://doi.org/10.4018/IJOSSP.2019040102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

Software expansion is rising with the help of the standard paradigm in the 21st century. The maximum contribution of software growth focuses mainly on object-oriented development methodologies. This paradigm helps the developer to develop code quickly and makes sure that the platform assists in producing a quality product. The software reusability metrics play a crucial role for software development. To overcome the scalability issues, researchers and developers both adopt a CK metrics suite to extract the software metrics to extract the features from the repositories. The main objective of this article is to extract the set of metrics from social media by using novel evolutionary techniques. Dissimilar features within this area are examined with a suitable research query that discovers the potential and extent.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.