30 Years of Software Refactoring Research:A Systematic Literature Review

Due to the growing complexity of software systems, there has been a dramatic increase and industry demand for tools and techniques on software refactoring in the last ten years, defined traditionally as a set of program transformations intended to improve the system design while preserving the behavior. Refactoring studies are expanded beyond code-level restructuring to be applied at different levels (architecture, model, requirements, etc.), adopted in many domains beyond the object-oriented paradigm (cloud computing, mobile, web, etc.), used in industrial settings and considered objectives beyond improving the design to include other non-functional requirements (e.g., improve performance, security, etc.). Thus, challenges to be addressed by refactoring work are, nowadays, beyond code transformation to include, but not limited to, scheduling the opportune time to carry refactoring, recommendations of specific refactoring activities, detection of refactoring opportunities, and testing the correctness of applied refactorings. Therefore, the refactoring research efforts are fragmented over several research communities, various domains, and objectives. To structure the field and existing research results, this paper provides a systematic literature review and analyzes the results of 3183 research papers on refactoring covering the last three decades to offer the most scalable and comprehensive literature review of existing refactoring research studies. Based on this survey, we created a taxonomy to classify the existing research, identified research trends, and highlighted gaps in the literature and avenues for further research.Comment: 23 page

30 Years of Software Refactoring Research: A Systematic Literature Review

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd

A Test-Driven Approach for Extracting Libraries of Reusable Components from Existing Applications

Abstract. In agile approaches such as Extreme Programming, time is not spent on making sure that system components can be reused in similar systems. Therefore, there is a need to investigate whether reuse can be achieved by extracting reusable assets from existing applications. This paper presents an approach that relies on refactoring and testing practices for extracting reusable assets from existing applications. The approach creates reusable APIs in a bottom-up fashion, on demand when a new application might benefit from component in an existing application. The extraction process is guided and supported by the usage examples and the testing scenarios in the existing application and the new one. The paper presents a case study, where the approach was used to extract components from the user interface of an existing application, wrap these components in an API, and use this API in the existing and new applications

F/OSS para el reuso: métricas, desarrollo de herramientas y marco para su evaluación

La disponibilidad de una creciente variedad de Software Libre y de Código Abierto (F/OSS por sus siglas en inglés) distribuidos bajo licencias que permiten explícitamente su modificación y el desarrollo de aplicaciones derivadas, abre nuevas posibilidades para el desarrollo con reutilización. Las características y la información disponible en relación a cada producto de F/OSS es muy heterogénea; no obstante, todas tienen en común la libre disponibilidad del código fuente. Esta tesis presenta nuevas formas de abordar el problema de evaluar y seleccionar productos de F/OSS, centrándose en dos aspectos: La utilización de métricas que pueden obtenerse del código fuente para la evaluación de F/OSS, de modo de caracterizar el diseño general de los productos de software que se consideren para la reutilización. La elaboración de un marco de trabajo para la selección y evaluación de software que sirva de base para una sistematización paulatina de la incorporación de la reutilización de F/OSS en diferentes procesos de desarrollo de software. A partir del estudio de una muestra de 560 versiones diferentes de aplicaciones de F/OSS, y en base al estudio de distribuciones de frecuencia, se proponen umbrales para métricas que reflejan aspectos generales del diseño de una aplicación. Específicamente, se consideran el promedio de la cantidad de métodos por clase y la proporción de referencias a métodos de otras clases respecto del total de métodos definidos en la aplicación. Estas dos medidas se refieren a la aplicación en su conjunto y no a clases o módulos particulares, lo que supone una utilidad diferente de estos valores respecto del papel que cumplen en otros aspectos de la gestión de proyectos de software. En relación al segundo aspecto, se presenta un marco de trabajo en tres etapas, a saber, la detección de oportunidades de reutilización, la búsqueda de recursos candidatos y la selección y evaluación. Este marco es de carácter general, pudiendo adaptarse a diferentes metodologías y contextos de desarrollo. La elaboración del marco parte de la realización de una experiencia de desarrollo con reutilización de F/OSS, la revisión de la literatura relacionada con las temáticas de selección de elementos reutilizables y la evaluación de éstos para su incorporación en nuevos desarrollos. Este marco se aplica posteriormente al desarrollo de una herramienta para computar un conjunto de métricas basadas en el código fuente para dar soporte al proceso de selección de F/OSS para la reutilización tomando en cuenta los umbrales propuestos previamente. De esta forma, se ofrece aquí una base para abordar la reutilización de F/OSS de manera de permitir la sistematización paulatina de esta práctica, brindando un criterio de valoración provisional basado en métricas obtenidas del código fuente.Facultad de Informátic

Explainable, Security-Aware and Dependency-Aware Framework for Intelligent Software Refactoring

As software systems continue to grow in size and complexity, their maintenance continues to become more challenging and costly. Even for the most technologically sophisticated and competent organizations, building and maintaining high-performing software applications with high-quality-code is an extremely challenging and expensive endeavor. Software Refactoring is widely recognized as the key component for maintaining high-quality software by restructuring existing code and reducing technical debt. However, refactoring is difficult to achieve and often neglected due to several limitations in the existing refactoring techniques that reduce their effectiveness. These limitation include, but not limited to, detecting refactoring opportunities, recommending specific refactoring activities, and explaining the recommended changes. Existing techniques are mainly focused on the use of quality metrics such as coupling, cohesion, and the Quality Metrics for Object Oriented Design (QMOOD). However, there are many other factors identified in this work to assist and facilitate different maintenance activities for developers: 1. To structure the refactoring field and existing research results, this dissertation provides the most scalable and comprehensive systematic literature review analyzing the results of 3183 research papers on refactoring covering the last three decades. Based on this survey, we created a taxonomy to classify the existing research, identified research trends and highlighted gaps in the literature for further research. 2. To draw attention to what should be the current refactoring research focus from the developers’ perspective, we carried out the first large scale refactoring study on the most popular online Q&A forum for developers, Stack Overflow. We collected and analyzed posts to identify what developers ask about refactoring, the challenges that practitioners face when refactoring software systems, and what should be the current refactoring research focus from the developers’ perspective. 3. To improve the detection of refactoring opportunities in terms of quality and security in the context of mobile apps, we designed a framework that recommends the files to be refactored based on user reviews. We also considered the detection of refactoring opportunities in the context of web services. We proposed a machine learning-based approach that helps service providers and subscribers predict the quality of service with the least costs. Furthermore, to help developers make an accurate assessment of the quality of their software systems and decide if the code should be refactored, we propose a clustering-based approach to automatically identify the preferred benchmark to use for the quality assessment of a project. 4. Regarding the refactoring generation process, we proposed different techniques to enhance the change operators and seeding mechanism by using the history of applied refactorings and incorporating refactoring dependencies in order to improve the quality of the refactoring solutions. We also introduced the security aspect when generating refactoring recommendations, by investigating the possible impact of improving different quality attributes on a set of security metrics and finding the best trade-off between them. In another approach, we recommend refactorings to prioritize fixing quality issues in security-critical files, improve quality attributes and remove code smells. All the above contributions were validated at the large scale on thousands of open source and industry projects in collaboration with industry partners and the open source community. The contributions of this dissertation are integrated in a cloud-based refactoring framework which is currently used by practitioners.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/171082/1/Chaima Abid Final Dissertation.pdfDescription of Chaima Abid Final Dissertation.pdf : Dissertatio