Feature level metrics based on size and similarity in software product line adoption

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 extr...

Teljes leírás

Elmentve itt :
Bibliográfiai részletek
Szerzők: Kicsi András
Csuvik Viktor
Testületi szerző: Conference of PhD students in computer science (11.) (2018) (Szeged)
Dokumentumtípus: Könyv része
Megjelent: 2018
Sorozat:Conference of PhD Students in Computer Science 11
Kulcsszavak:Számítástechnika - előadáskivonat
Online Access:http://acta.bibl.u-szeged.hu/61756
Leíró adatok
Tartalmi kivonat: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.
Terjedelem/Fizikai jellemzők:25-28