Structural Complexity Attribute Classification Framework (SCACF) for Sassy Cascading Style Sheets

Autor: Kelvin Kabeti Omieno, John Gichuki Ndia, Geoffrey Muchiri Muketha
Rok vydání: 2020
Předmět:
DOI: 10.5281/zenodo.3828623
Popis: Several researchers have proposed the various classes of software attributes to guide in the derivation of metrics for software products. These existing classifications have targeted traditional software paradigms such as procedural and object-oriented software. Sassy cascading style sheets (SCSS) has unique features since it combines Cascading style sheets (CSS) features with traditional software features such as variables, functions and control flows. Due to this uniqueness, there arises a need to develop a new classification scheme that can be effectively used to classify all the possible structural attributes for Sassy cascading style sheets. The aim of this paper, therefore, is to develop and validate a comprehensive software complexity attributes classification framework for SCSS. The new framework was validated through an online expert opinion survey, where thirteen SCSS experts were involved. Results show that the proposed framework is complete and effective to guide metrics researchers in defining new metrics for SCSS
Databáze: OpenAIRE