Kicsi, András and Csuvik, Viktor: Feature level metrics based on size and similarity in software product line adoption. In: Conference of PhD Students in Computer Science, (11). pp. 25-28. (2018)
|
Cikk, tanulmány, mű
cscs_2018_038-041.pdf Download (287kB) | Preview |
Abstract
Introducing software product lines is a natural way to cope with a large number of software variants and hard maintenance. This task can become more complicated with a fourth generation language, namely Magic in our case. Feature extraction is an important task of product line adoption, and the extracted features can amount to large proportions of the code and can be hard to contemplate, thus appropriate methods become necessary to ease the handling of the information gained. In this work we present some feature level metrics aiming to highlight valuable information on both the results attained through extraction and the features themselves which can be used in furthering the process of product line adoption. We present some metrics based on size and pairwise similarity of the features of four different variants of the same system. The knowledge of these metrics, properly measured and used can be vital in aiding product line adoption.
| Item Type: | Article |
|---|---|
| Journal or Publication Title: | Conference of PhD Students in Computer Science |
| Date: | 2018 |
| Volume: | 11 |
| Page Range: | pp. 25-28 |
| Event Title: | Conference of PhD students in computer science (11.) (2018) (Szeged) |
| Uncontrolled Keywords: | Számítástechnika - előadáskivonat |
| Additional Information: | Bibliogr.: p. 27-28. ; összefoglalás angol nyelven |
| Date Deposited: | 2019. Oct. 28. 10:52 |
| Last Modified: | 2019. Oct. 28. 10:52 |
| URI: | http://acta.bibl.u-szeged.hu/id/eprint/61756 |
Actions (login required)
 |
View Item |
