What is he best known for?
The fields of study he is best known for:
- Software
- Artificial intelligence
- Operating system
His primary scientific interests are in Software, Empirical research, Source code, Software engineering and Code smell.
His work deals with themes such as Artifact, Data mining, Identification and Information retrieval, which intersect with Software.
His Empirical research study combines topics in areas such as Recommender system, World Wide Web, Artificial intelligence, User experience design and Mining software repositories.
His Source code research incorporates elements of Software maintenance and Heuristics.
His research investigates the link between Software engineering and topics such as Software system that cross with problems in Code refactoring, Unified Modeling Language, Maintainability and Reliability engineering.
His Code smell study combines topics from a wide range of disciplines, such as Computer security, Code and Test.
His most cited work include:
- Recovering traceability links in software artifact management systems using information retrieval methods (337 citations)
- API change and fault proneness: a threat to the success of Android apps (213 citations)
- How to effectively use topic models for software engineering tasks? an approach based on genetic algorithms (203 citations)
What are the main themes of his work throughout his whole career to date?
Rocco Oliveto mainly investigates Software, Software engineering, Source code, Traceability and Data mining.
His studies in Software integrate themes in fields like Empirical research, World Wide Web, Information retrieval and Documentation.
His work carried out in the field of Software engineering brings together such families of science as Software system, Software quality, Software maintenance, Software development and Software evolution.
Rocco Oliveto has included themes like Java, Static program analysis, Code smell and Code refactoring in his Source code study.
The various areas that Rocco Oliveto examines in his Traceability study include Requirements traceability, Reverse semantic traceability, Tracing, Vector space model and Search engine indexing.
His Data mining research is multidisciplinary, incorporating elements of Machine learning, False positive paradox and Artificial intelligence.
He most often published in these fields:
- Software (40.78%)
- Software engineering (33.01%)
- Source code (28.64%)
What were the highlights of his more recent work (between 2017-2021)?
- Software engineering (33.01%)
- Code (11.65%)
- Software (40.78%)
In recent papers he was focusing on the following fields of study:
His main research concerns Software engineering, Code, Software, Code smell and Source code.
The study incorporates disciplines such as Sentiment analysis, Android, Root cause and Mobile apps in addition to Software engineering.
His Software research integrates issues from Empirical research and World Wide Web.
His Code smell research includes themes of Software system, Maintainability, Data science and Software evolution.
His biological study spans a wide range of topics, including Readability, Information retrieval, Internet privacy and Code refactoring.
Rocco Oliveto interconnects Program comprehension and Software maintenance in the investigation of issues within Information retrieval.
Between 2017 and 2021, his most popular works were:
- On the diffuseness and the impact on maintainability of code smells: a large scale empirical investigation (117 citations)
- Sentiment analysis for software engineering: how far can we go? (76 citations)
- A Developer Centered Bug Prediction Model (58 citations)
In his most recent research, the most cited papers focused on:
- Software
- Artificial intelligence
- Operating system
His scientific interests lie mostly in Code smell, Software, Software engineering, Code and Artificial intelligence.
His Code smell research is multidisciplinary, relying on both Maintainability, Data science and Software evolution.
His study in Empirical research extends to Software with its themes.
His research in Empirical research intersects with topics in Data mining, Component-based software engineering, Exploit, Entropy and Mining software repositories.
Rocco Oliveto combines subjects such as Sentiment analysis, Software system, Personalization and Source code with his study of Software engineering.
His study in the field of Deep learning also crosses realms of Set.
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