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ThinkMind // ICSEA 2020, The Fifteenth International Conference on Software Engineering Advances // View article icsea_2020_1_220_10115

Code Quality Metrics Derived from Software Design

Authors:
Omar Masmali
Omar Badreddin

Keywords: code quality; model-driven engineering; software quality metrics; UML class diagram; software design.

Abstract:
Code smells are assumed to indicate bad design that can cause an unsustainable system. Many studies have tailored fixed threshold values for code smell metrics. However, these threshold values have ignored the fact that every system is unique, and it cannot be dynamically evolved throughout the codebase life cycle. This paper presents a novel approach that formulates a dynamic code quality metrics with thresholds that are derived from software design. The first step in this approach is to measure the complexity of the design. Many researchers had developed many complexity metrics to measure the level of complexity in software models. Most of these metrics are limited and focus on counting the number of elements in each design, ignoring the unique characteristics of these elements and their interactions. In this study, we also propose a new methodology to measure the complexity of any software design. This measurement approach is based on evaluating each element in any class diagram by assigning a complexity rate. Finally, we propose a methodology to evaluate the effectiveness of this approach.

Pages: 141 to 146

Copyright: Copyright (c) IARIA, 2020

Publication date: October 18, 2020

Published in: conference

ISSN: 2308-4235

ISBN: 978-1-61208-827-3

Location: Porto, Portugal

Dates: from October 18, 2020 to October 22, 2020

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