Towards Increase in Quality by Preprocessed Source Code and Measurement Analysis of Software Applications

TL;DR

This paper presents a measurement analysis approach to improve software quality by analyzing preprocessed source code, identifying complexities, and visualizing results to address fault proneness and variability issues.

Contribution

It introduces a novel measurement analysis method and a prototype tool for analyzing preprocessed source code to enhance software quality and manage complexity.

Findings

Prototype effectively analyzes source code complexities.

Visualization aids in understanding code structure.

Experiment validates the approach's effectiveness.

Abstract

In this paper two intensive problems faced during software application's analysis and development process arose by the software industry are briefly conversed i.e. identification of fault proneness and increase in rate of variability in the source code of traditional and product line applications. To contribute in the field of software application analysis and development, and to mitigate the aforementioned hurdles, a measurement analysis based approach is discussed in this paper. Furthermore, a prototype is developed based on the concepts of discussed approach i.e. analyzing preprocessed source code characteristics, identifying additional level of complexities using several procedural and object oriented source code measures and visualizing obtained results in different diagrams e.g. bar charts, file maps and graphs etc. Developed prototype is discussed in detail in this paper and validated by means of an experiment as well.