RefDiff: Detecting Refactorings in Version Histories

Refactoring is a well-known technique that is widely adopted by software engineers to improve the design and enable the evolution of a system. Knowing which refactoring operations were applied in a code change is a valuable information to understand software evolution, adapt software components, merge code changes, and other applications. In this paper, we present RefDiff, an automated approach that identifies refactorings performed between two code revisions in a git repository. RefDiff employs a combination of heuristics based on static analysis and code similarity to detect 13 well-known refactoring types. In an evaluation using an oracle of 448 known refactoring operations, distributed across seven Java projects, our approach achieved precision of 100% and recall of 88%. Moreover, our evaluation suggests that RefDiff has superior precision and recall than existing state-of-the-art approaches.Comment: Paper accepted at 14th International Conference on Mining Software Repositories (MSR), pages 1-11, 201

Refactoring for Reuse: An Empirical Study

Refactoring is the de-facto practice to optimize software health. While several studies propose refactoring strategies to optimize software design through applying design patterns and removing design defects, little is known about how developers actually refactor their code to improve its reuse. Therefore, we extract, from 1,828 open source projects, a set of refactorings that were intended to improve the software reusability. We analyze the impact of reusability refactorings on the state-of-the-art reusability metrics, and we compare the distribution of reusability refactoring types, with the distribution of the remaining mainstream refactorings. Overall, we found that the distribution of refactoring types, applied in the context of reusability, is different from the distribution of refactoring types in mainstream development. In the refactorings performed to improve reusability, source files are subject to more design level types of refactorings. Reusability refactorings significantly impact, high-level code elements, such as packages, classes, and methods, while typical refactorings, impact all code elements, including identifiers, and parameters. These findings provide practical insights into the current practice of refactoring in the context of code reuse involving the act of refactoring

PROGRAM INSPECTION AND TESTING TECHNIQUES FOR CODE CLONES AND REFACTORINGS IN EVOLVING SOFTWARE

Developers often perform copy-and-paste activities. This practice causes the similar code fragment (aka code clones) to be scattered throughout a code base. Refactoring for clone removal is beneficial, preventing clones from having negative effects on software quality, such as hidden bug propagation and unintentional inconsistent changes. However, recent research has provided evidence that factoring out clones does not always reduce the risk of introducing defects, and it is often difficult or impossible to remove clones using standard refactoring techniques. To investigate which or how clones can be refactored, developers typically spend a significant amount of their time managing individual clone instances or clone groups scattered across a large code base. To address the problem, this research proposes two techniques to inspect and validate refactoring changes. First, we propose a technique for managing clone refactorings, Pattern-based clone Refactoring Inspection (PRI), using refactoring pattern templates. By matching the refactoring pattern templates against a code base, it summarizes refactoring changes of clones, and detects the clone instances not consistently factored out as potential anomalies. Second, we propose Refactoring Investigation and Testing technique, called RIT. RIT improves the testing efficiency for validating refactoring changes. RIT uses PRI to identify refactorings by analyzing original and edited versions of a program. It then uses the semantic impact of a set of identified refactoring changes to detect tests whose behavior may have been affected and modified by refactoring edits. Given each failed asserts, RIT helps developers focus their attention on logically related program statements by applying program slicing for minimizing each test. For debugging purposes, RIT determines specific failure-inducing refactoring edits, separating from other changes that only affect other asserts or tests

Behind the Intents: An In-depth Empirical Study on Software Refactoring in Modern Code Review

Code refactorings are of pivotal importance in modern code review. Developers may preserve, revisit, add or undo refactorings through changes’ revisions. Their goal is to certify that the driving intent of a code change is properly achieved. Developers’ intents behind refactorings may vary from pure structural improvement to facilitating feature additions and bug fixes. However, there is little understanding of the refactoring practices performed by developers during the code review process. It is also unclear whether the developers’ intents influence the selection, composition, and evolution of refactorings during the review of a code change. Through mining 1,780 reviewed code changes from 6 systems pertaining to two large open-source communities, we report the first in-depth empirical study on software refactoring during code review. We inspected and classified the developers’ intents behind each code change into 7 distinct categories. By analyzing data generated during the complete reviewing process, we observe: (i) how refactorings are selected, composed and evolved throughout each code change, and (ii) how developers’ intents are related to these decisions. For instance, our analysis shows developers regularly apply non-trivial sequences of refactorings that crosscut multiple code elements (i.e., widely scattered in the program) to support a single feature addition. Moreover, we observed that new developers’ intents commonly emerge during the code review process, influencing how developers select and compose their refactorings to achieve the new and adapted goals. Finally, we provide an enriched dataset that allows researchers to investigate the context and motivations behind refactoring operations during the code review process

Detection of microservice smells through static analysis

A arquitetura de microsserviços é um modelo arquitetural promissor na área de software, atraindo desenvolvedores e empresas para os seus princípios convincentes. As suas vantagens residem no potencial para melhorar a escalabilidade, a flexibilidade e a agilidade, alinhando se com as exigências em constante evolução da era digital. No entanto, navegar entre as complexidades dos microsserviços pode ser uma tarefa desafiante, especialmente à medida que este campo continua a evoluir. Um dos principais desafios advém da complexidade inerente aos microsserviços, em que o seu grande número e interdependências podem introduzir novas camadas de complexidade. Além disso, a rápida expansão dos microsserviços, juntamente com a necessidade de aproveitar as suas vantagens de forma eficaz, exige uma compreensão mais profunda das potenciais ameaças e problemas que podem surgir. Para tirar verdadeiramente partido das vantagens dos microsserviços, é essencial enfrentar estes desafios e garantir que o desenvolvimento e a adoção de microsserviços sejam bem-sucedidos. O presente documento pretende explorar a área dos smells da arquitetura de microsserviços que desempenham um papel tão importante na dívida técnica dirigida à área dos microsserviços. Embarca numa exploração de investigação abrangente, explorando o domínio dos smells de microsserviços. Esta investigação serve como base para melhorar um catálogo de smells de microsserviços. Esta investigação abrangente obtém dados de duas fontes primárias: systematic mapping study e um questionário a profissionais da área. Este último envolveu 31 profissionais experientes com uma experiência substancial no domínio dos microsserviços. Além disso, são descritos o desenvolvimento e o aperfeiçoamento de uma ferramenta especificamente concebida para identificar e resolver problemas relacionados com os microsserviços. Esta ferramenta destina-se a melhorar o desempenho dos programadores durante o desenvolvimento e a implementação da arquitetura de microsserviços. Por último, o documento inclui uma avaliação do desempenho da ferramenta. Trata-se de uma análise comparativa efetuada antes e depois das melhorias introduzidas na ferramenta. A eficácia da ferramenta será avaliada utilizando o mesmo benchmarking de microsserviços utilizado anteriormente, para além de outro benchmarking para garantir uma avaliação abrangente.The microservices architecture stands as a beacon of promise in the software landscape, drawing developers and companies towards its compelling principles. Its appeal lies in the potential for improved scalability, flexibility, and agility, aligning with the ever-evolving demands of the digital age. However, navigating the intricacies of microservices can be a challenging task, especially as this field continues to evolve. A key challenge arises from the inherent complexity of microservices, where their sheer number and interdependencies can introduce new layers of intricacy. Furthermore, the rapid expansion of microservices, coupled with the need to harness their advantages effectively, demands a deeper understanding of the potential pitfalls and issues that may emerge. To truly unlock the benefits of microservices, it is essential to address these challenges head-on and ensure a successful journey in the world of microservices development and adoption. The present document intends to explore the area of microservice architecture smells that play such an important role in the technical debt directed to the area of microservices. It embarks on a comprehensive research exploration, delving into the realm of microservice smells. This research serves as the cornerstone for enhancing a microservice smell catalogue. This comprehensive research draws data from two primary sources: a systematic mapping research and an industry survey. The latter involves 31 seasoned professionals with substantial experience in the field of microservices. Moreover, the development and enhancement of a tool specifically designed to identify and address issues related to microservices is described. This tool is aimed at improving developers' performance throughout the development and implementation of microservices architecture. Finally, the document includes an evaluation of the tool's performance. This involves a comparative analysis conducted before and after the tool's enhancements. The tool's effectiveness will be assessed using the same microservice benchmarking as previously employed, in addition to another benchmark to ensure a comprehensive evaluation