Design Smell Analysis for Developing and Established Open Source Java Software

TL;DR

This paper presents a mechanism and tool for identifying and comparing the prevalence of design smells in developing versus established open-source Java software, revealing different dominant smell types in each stage.

Contribution

It introduces a novel approach and tool for detecting and analyzing the frequency of design smells in different development stages of open-source Java projects.

Findings

Developing software mainly exhibits four specific types of design smells.

Established software predominantly contains four other types of design smells.

The detection tool achieved precision between 72.9% and 84.1%.

Abstract

Software design smells are design attributes which violate the fundamental design principles. Design smells are a key cause of design debt. Although the activities of design smell identification and measurement are predominantly considered in current literature, those which identify and communicate which design smells occur more frequently in newly developing software and which ones are more dominant in established software have been studied to a limited extent. This research describes a mechanism for identifying the design smells that are more prevalent in developing and established software respectively. A tool is provided which is used for design smell detection by analyzing large volumes of source code. More specifically, 164,609 Lines of Code (LoC) and 5,712 class files of six developing and 244,930 LoC and 12,048 class files of five established open-source Java software are analyzed. Obtained results show that out of the 4,020 occurrences of smells that were made for nine preselected types of design smells, 1,643 design smells were detected for developing software, which mainly consisted of four specific types of smells. For established software, 2,397 design smells were observed which predominantly consisted of four other types of smells. The remaining design smell was equally prevalent in both developing and established software. Desirable precision values ranging from 72.9% to 84.1% were obtained for the tool.