arXiv subjects

Leonardo Murta

Publications and source records attributed to Leonardo Murta.

5 recordsLinked to original sources

arXiv2026

On the Influence of Refactoring Types on Merge Effort

Modern software development involves parallel work and concurrent changes, requiring code merging. Prior studies report that 10% to 20% of merge attempts result in conflicts, often requiring manual intervention. The literature explores factors that generate conflicts, including refactorings, but does not analyze how individual refactoring types influence the manual effort required to resolve them. We analyzed 64 open-source Java projects and applied association rule mining to measure the strength of associations between specific refactoring types and merge effort. Our results show that refactoring types relate to merge effort with varying strength. In particular, Rename Attribute, Move Class, Extract Variable, Change Return Type, and Split Parameter exhibit some of the strongest associations, especially when a higher number of such refactorings is present in the merge branches. We also find that both the number of refactorings and their diversity independently increase merge effort, both in terms of occurrence and intensity. Additionally, the co-occurrence of refactorings across parallel branches is associated with higher merge effort, particularly when combining structural transformations with changes to method signatures and data-structure representations, whereas more localized changes are less frequent in the most impactful combinations.

cs.SE↗

arXiv2026

Analyzing the Adoption of Database Management Systems Throughout the History of Open Source Projects

Database Management Systems (DBMSs) are widely used to store, retrieve, and manage the data handled by modern applications. Although prior work has studied the co-evolution of DBMSs and application source code, less is known about DBMS adoption, co-use, and replacement in real systems. This paper presents a historical study of DBMS usage in 362 popular open-source Java projects hosted on GitHub. We investigated the adoption of the top DBMSs ranked by DB-Engines, covering relational and non-relational systems. Using source-code heuristics, we analyzed DBMS popularity, stability, migration patterns, co-occurrence, and the role of Object-Relational Mappers (ORMs). Our findings show that MySQL and PostgreSQL are the most popular DBMSs in our corpus. Among non-relational DBMSs, Redis and MongoDB are the most frequently used and tend to remain stable after adoption. In contrast, systems such as HyperSQL are more often replaced as projects evolve. We also observed frequent co-use of multiple DBMSs, suggesting patterns of polyglot persistence in which projects combine systems to handle different data needs. Finally, we found that ORM frameworks are commonly used to mediate interactions between applications and DBMSs. Overall, our study provides empirical evidence on how DBMSs are adopted, combined, and replaced over time, offering guidance for developers, architects, educators, and DBMS vendors.

cs.SE↗

arXiv2023

Do code refactorings influence the merge effort?

In collaborative software development, multiple contributors frequently change the source code in parallel to implement new features, fix bugs, refactor existing code, and make other changes. These simultaneous changes need to be merged into the same version of the source code. However, the merge operation can fail, and developer intervention is required to resolve the conflicts. Studies in the literature show that 10 to 20 percent of all merge attempts result in conflicts, which require the manual developer's intervention to complete the process. In this paper, we concern about a specific type of change that affects the structure of the source code and has the potential to increase the merge effort: code refactorings. We analyze the relationship between the occurrence of refactorings and the merge effort. To do so, we applied a data mining technique called association rule extraction to find patterns of behavior that allow us to analyze the influence of refactorings on the merge effort. Our experiments extracted association rules from 40,248 merge commits that occurred in 28 popular open-source projects. The results indicate that: (i) the occurrence of refactorings increases the chances of having merge effort; (ii) the more refactorings, the greater the chances of effort; (iii) the more refactorings, the greater the effort; and (iv) parallel refactorings increase even more the chances of having effort, as well as the intensity of it. The results obtained may suggest behavioral changes in the way refactorings are implemented by developer teams. In addition, they can indicate possible ways to improve tools that support code merging and those that recommend refactorings, considering the number of refactorings and merge effort attributes.

cs.SE↗

arXiv2020

On the Performance of Hybrid Search Strategies for Systematic Literature Reviews in Software Engineering

Context: When conducting a Systematic Literature Review (SLR), researchers usually face the challenge of designing a search strategy that appropriately balances result quality and review effort. Using digital library (or database) searches or snowballing alone may not be enough to achieve high-quality results. On the other hand, using both digital library searches and snowballing together may increase the overall review effort. Objective: The goal of this research is to propose and evaluate hybrid search strategies that selectively combine database searches with snowballing. Method: We propose four hybrid search strategies combining database searches in digital libraries with iterative, parallel, or sequential backward and forward snowballing. We simulated the strategies over three existing SLRs in SE that adopted both database searches and snowballing. We compared the outcome of digital library searches, snowballing, and hybrid strategies using precision, recall, and F-measure to investigate the performance of each strategy. Results: Our results show that, for the analyzed SLRs, combining database searches from the Scopus digital library with parallel or sequential snowballing achieved the most appropriate balance of precision and recall. Conclusion: We put forward that, depending on the goals of the SLR and the available resources, using a hybrid search strategy involving a representative digital library and parallel or sequential snowballing tends to represent an appropriate alternative to be used when searching for evidence in SLRs.

cs.DL↗

arXiv2018

An Infrastructure for Software Release Analysis through Provenance Graphs

Nowadays, quickly evolving and delivering software through a continuous delivery process is a competitive advantage and a way to keep software updated in response to the frequent changes in customers' requirements. However, the faster the software release cycle, the more challenging to track software evolution. In this paper, we propose Releasy, a tool that aims at supporting projects that use continuous delivery by generating and reporting their release provenance. The provenance generated by Releasy allows graphical visualization of the software evolution and supports queries to discover implicit information, such as the implemented features of each release and the involved developers. We also show in this paper a preliminary evaluation of Releasy in action, generating the changelog of an open source project with the provenance collected by our tool.

cs.SE↗