Severity Level Analysis in Cross-Platform and Native Mobile Development: Insights from Dart, Java, and Kotlin = 교차 플랫폼 및 네이티브 모바일 개발에서 심각도 수준 분석: Dart, Java 및 Kotlin의 통찰

다국어 초록 (Multilingual Abstract)

Though many approaches to developing mobile applications have been suggested up to now, developers have difficulties selecting the right one. This study compares native and cross-platform application development approaches, particularly focusing on the shift in preference from Java to Kotlin and the increasing use of Flutter. This research offers practical insights into factors influencing developers’ choice of programming languages and frameworks in mobile application development by creating identical applications us- ing Java, Kotlin, and Dart (Flutter). Furthermore, this study explores the best practices for development by examining the quality of code in 45 open-source GitHub reposito- ries. The study evaluates LOC and code smells using semi-automated SonarQube assess- ments, including the measurement of severity levels, to determine the effects of selecting a specific language or framework on code smells and development efficiency. Preliminary findings show differences in the quality of the code produced by the two approaches, offering developers useful information on reducing code smells and improving project quality.

국문 초록 (Abstract)

모바일 앱 개발 방법에 대해 많은 접근법이 제안되었지만, 개발자들은 적합한 방법 선택에 어려움을 겪고 있다. 이 연구는 네이티브 및 크로스 플랫폼 어플리케이션 개발 접근 방식을 비교하며, 특히 Java에서 Kotlin으로의 선호도 변화와 Flutter의 사용 증가에 중점을 두고 비교한다. 이 연구는 Java, Kotlin, Dart(Flutter)를 사용하여 같은 어플리케이션을 작성 함으로써, 모바일 어플리케이션 개발에서 프로그래밍 언어 및 프레임워크 선택에 영향을 미치는 요인에 관한 실질적인 통찰을 제공한다. 또한, 이 연구는 45개의 GitHub 공개 소 스 프로그램의 코드 품질도 검사함으로써 모범 개발 사례를 모색한다. 구체적으로, 반자동 SonarQube 평가를 사용하여 LOC 및 코드 스멜을 평가하고, 이를 통해 특정 언어나 프 레임워크 선택에 따라 코드의 유지보수 및 개발 효율성에 미치는 영향을 탐구한다. 실험 결과, 작성된 코드 품질의 차이를 알 수 있었다. 본 연구는 코드 스멜을 줄이고 프로젝트 유지보수를 개선하는 데 적합한 프로그래밍 언어와 프레임워크를 선택하는 데 도움이 될 것으로 기대된다.

목차 (Table of Contents)

• I Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
• 1.1 Overview of Mobile Application Development . . . . . . . . . . . . 1
• 1.2 Study Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
• 1.3 Methodology, Significance, and Structure of Thesis . . . . . . . . . 5
• II Literature Review . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
• 2.1 Java . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
• 2.2 Kotlin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
• 2.3 Dart(Flutter) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
• 2.4 Previous Research . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
• III Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
• 3.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
• 3.2 Identical Mobile Application Development . . . . . . . . . . . . . . 20
• 3.2.1 Project Planning. . . . . . . . . . . . . . . . . . . . . . . 20
• 3.2.2 Flutter Application Development . . . . . . . . . . . . . . 23
• 3.2.3 Kotlin Application Development . . . . . . . . . . . . . . 25
• 3.2.4 Java Application Development . . . . . . . . . . . . . . . 27
• 3.3 SonarQube Code Inspection and Open Source Projects . . . . . . . 29
• 3.3.1 Issue Severity in SonarQube . . . . . . . . . . . . . . . . 30
• 3.3.2 Setting Up SonarQube Environment . . . . . . . . . . . . 31
• 3.3.3 Applying SonarQube Analysis to the Kanban Board Project 32
• 3.4 Setting Up an Automated Pipeline for SonarQube Analysis of Open Source Projects . . 34
• IV Results of Comparative Analysis . . . . . . . . . . . . . . . . . . . . . . . 36
• 4.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
• 4.2 Results from Identical Application Development . . . . . . . . . . 36
• 4.2.1 Code Quality Analysis . . . . . . . . . . . . . . . . . . . . 37
• 4.2.2 Task Model Implementation . . . . . . . . . . . . . . . . 38
• 4.2.3 Application Size and Performance . . . . . . . . . . . . . 38
• 4.3 SonarQube Implementation in Open Source Projects . . . . . . . . 39
• 4.3.1 Java Projects Analysis . . . . . . . . . . . . . . . . . . . 39
• 4.3.2 Kotlin Project Analysis . . . . . . . . . . . . . . . . . . . 40
• 4.3.3 Flutter Projects Analysis . . . . . . . . . . . . . . . . . . 40
• 4.3.4 Comparative Graph and Discussion . . . . . . . . . . . . 42
• V Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
• 5.1 Interpretation of Results . . . . . . . . . . . . . . . . . . . . . . . . 43
• 5.2 Recommendations for Future Development Practices . . . . . . . . 44
• 5.3 Proposed Enhancements for Future Research . . . . . . . . . . . . 44
• 5.4 Reflection on Methodological Approaches . . . . . . . . . . . . . . 45
• VI Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
• I Project Listings for Automated SonarQube Analysis . . . . . . . . . . . . 57
• II Python Script for Project Automation and Configuration . . . . . . . . . 60
• III Python Script for Data Retrieval and Report Generation . . . . . . . . . . 65
• IV Implementation Details of Task Models . . . . . . . . . . . . . . . . . . . 69