What is he best known for?
The fields of study he is best known for:
- Software
- Programming language
- Software engineering
His main research concerns Software engineering, Aspect-oriented programming, Software system, Programming language and Software development.
He has included themes like Software maintenance, Software metric, Object-oriented programming and Software architecture, Software in his Software engineering study.
His research in Software maintenance intersects with topics in Reliability engineering and Code refactoring.
His Aspect-oriented programming research is multidisciplinary, incorporating elements of Maintainability, Cohesion, Modular programming and Separation of concerns.
His Software system study combines topics from a wide range of disciplines, such as Source code and Code smell.
His work on Exception handling and AspectJ as part of general Programming language study is frequently linked to Exploratory research, bridging the gap between disciplines.
His most cited work include:
- Evolving software product lines with aspects: an empirical study on design stability (306 citations)
- Modularizing design patterns with aspects: a quantitative study (265 citations)
- On the Reuse and Maintenance of Aspect-Oriented Software: An Assessment Framework (215 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Software engineering, Software, Software development, Software system and Programming language.
His Software engineering study integrates concerns from other disciplines, such as Aspect-oriented programming, Systems engineering, Source code, Software architecture and Software construction.
In his study, Reusability is inextricably linked to Maintainability, which falls within the broad field of Aspect-oriented programming.
His work is dedicated to discovering how Source code, Code smell are connected with Identification, Data science and Empirical research and other disciplines.
The study incorporates disciplines such as Architectural pattern and Resource-oriented architecture in addition to Software architecture.
His Software study frequently intersects with other fields, such as Stability.
He most often published in these fields:
- Software engineering (51.49%)
- Software (25.30%)
- Software development (19.94%)
What were the highlights of his more recent work (between 2018-2021)?
- Software engineering (51.49%)
- Code refactoring (12.50%)
- Code smell (11.90%)
In recent papers he was focusing on the following fields of study:
Alessandro Garcia focuses on Software engineering, Code refactoring, Code smell, Code and Software.
The concepts of his Software engineering study are interwoven with issues in Documentation, Commit and Source code.
He has included themes like God object, Empirical research and Cohesion in his Code refactoring study.
His work carried out in the field of Code smell brings together such families of science as Maintainability, Code review, Task and Identification.
His research investigates the connection between Code and topics such as Programming language that intersect with problems in Test case and Natural language.
He has researched Software in several fields, including Eye tracking, Bridging, Task analysis and Human–computer interaction.
Between 2018 and 2021, his most popular works were:
- A Quantitative Study on Characteristics and Effect of Batch Refactoring on Code Smells (14 citations)
- Analysis of the criteria adopted in industry to extract microservices (13 citations)
- Extraction of Configurable and Reusable Microservices from Legacy Systems: An Exploratory Study (9 citations)
In his most recent research, the most cited papers focused on:
- Software
- Programming language
- Software engineering
His primary areas of investigation include Code refactoring, Code smell, Software engineering, Code and Code review.
His Code refactoring research includes themes of Agile software development, Key and Java.
His Code smell study improves the overall literature in Software.
His Software research integrates issues from Class, Isolation and Personalization.
His Software engineering study combines topics in areas such as Statistical hypothesis testing and Empirical research.
His Code study combines topics from a wide range of disciplines, such as Ranking and Source code.
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