10 citations · 32 across the 21 of their papers we have counts for
22 papers
Identifying and Characterizing Semantic Clones of Solidity Functions
Ermanno Francesco Sannini, Francesco Salzano, Simone Scalabrino +4
Smart Contracts are essential blockchain components, mainly written in Solidity. The high availability of public Solidity code leads to frequent reuse and high clone ratios. Since…
On the Impact of Code Comments for Automated Bug-Fixing: An Empirical Study
Antonio Vitale, Emanuela Guglielmi, Simone Scalabrino +1
Large Language Models (LLMs) are increasingly relevant in Software Engineering research and practice, with Automated Bug Fixing (ABF) being one of their key applications. ABF invol…
Toward Explaining Large Language Models in Software Engineering Tasks
Antonio Vitale, Khai-Nguyen Nguyen, Denys Poshyvanyk +3
Recent progress in Large Language Models (LLMs) has substantially advanced the automation of software engineering (SE) tasks, enabling complex activities such as code generation an…
Bug Detective and Quality Coach: Developers' Mental Models of AI-Assisted IDE Tools
Paolo Buono, Mary Cerullo, Stefano Cirillo +7
AI-assisted tools support developers in performing cognitively demanding tasks such as bug detection and code readability assessment. Despite the advancements in the technical char…
Beyond Code Similarity: Benchmarking the Plausibility, Efficiency, and Complexity of LLM-Generated Smart Contracts
Francesco Salzano, Simone Scalabrino, Rocco Oliveto +1
Smart Contracts are critical components of blockchain ecosystems, with Solidity as the dominant programming language. While LLMs excel at general-purpose code generation, the uniqu…
An empirical analysis of vulnerability detection tools for solidity smart contracts
Francesco Salzano, Cosmo Kevin Antenucci, Simone Scalabrino +3
The rapid adoption of blockchain technology highlighted the importance of ensuring the security of smart contracts due to their critical role in automated business logic execution…
How do Copilot Suggestions Impact Developers' Frustration and Productivity?
Emanuela Guglielmi, Venera Arnoudova, Gabriele Bavota +2
Context. AI-based development tools, such as GitHub Copilot, are transforming the software development process by offering real-time code suggestions. These tools promise to improv…
Identifying and Replicating Code Patterns Driving Performance Regressions in Software Systems
Denivan Campos, Luana Martins, Emanuela Guglielmi +6
Context: Performance regressions negatively impact execution time and memory usage of software systems. Nevertheless, there is a lack of systematic methods to evaluate the effectiv…
Personalized Code Readability Assessment: Are We There Yet?
Antonio Vitale, Emanuela Guglielmi, Rocco Oliveto +1
Unreadable code could be a breeding ground for errors. Thus, previous work defined approaches based on machine learning to automatically assess code readability that can warn devel…
Optimizing Datasets for Code Summarization: Is Code-Comment Coherence Enough?
Antonio Vitale, Antonio Mastropaolo, Rocco Oliveto +2
Automated code summarization is a long-standing goal for code comprehension. This task automatically generates documentation using a given method. Deep Learning (DL)-based approach…
Fixing Smart Contract Vulnerabilities: A Comparative Analysis of Literature and Developer's Practices
Francesco Salzano, Simone Scalabrino, Rocco Oliveto +1
Smart Contracts are programs running logic in the Blockchain network by executing operations through immutable transactions. The Blockchain network validates such transactions, sto…
Using Gameplay Videos for Detecting Issues in Video Games
Emanuela Guglielmi, Simone Scalabrino, Gabriele Bavota +1
Context. The game industry is increasingly growing in recent years. Every day, millions of people play video games, not only as a hobby, but also for professional competitions (e.g…
Automatically Generating Dockerfiles via Deep Learning: Challenges and Promises
Giovanni Rosa, Antonio Mastropaolo, Simone Scalabrino +2
Containerization allows developers to define the execution environment in which their software needs to be installed. Docker is the leading platform in this field, and developers t…
Source Code Recommender Systems: The Practitioners' Perspective
Matteo Ciniselli, Luca Pascarella, Emad Aghajani +3
The automatic generation of source code is one of the long-lasting dreams in software engineering research. Several techniques have been proposed to speed up the writing of new cod…
On the Robustness of Code Generation Techniques: An Empirical Study on GitHub Copilot
Antonio Mastropaolo, Luca Pascarella, Emanuela Guglielmi +4
Software engineering research has always being concerned with the improvement of code completion approaches, which suggest the next tokens a developer will likely type while coding…
Fixing Dockerfile Smells: An Empirical Study
Giovanni Rosa, Simone Scalabrino, Rocco Oliveto
Background. Containerization technologies are widely adopted in the DevOps workflow. The most commonly used one is Docker, which requires developers to define a specification file…
Using Transfer Learning for Code-Related Tasks
Antonio Mastropaolo, Nathan Cooper, David Nader Palacio +4
Deep learning (DL) techniques have been used to support several code-related tasks such as code summarization and bug-fixing. In particular, pre-trained transformer models are on t…
Towards Using Gameplay Videos for Detecting Issues in Video Games
Emanuela Guglielmi, Simone Scalabrino, Gabriele Bavota +1
Context. The game industry is increasingly growing in recent years. Every day, millions of people play video games, not only as a hobby, but also for professional competitions (e.g…
Using Reinforcement Learning for Load Testing of Video Games
Rosalia Tufano, Simone Scalabrino, Luca Pascarella +3
Different from what happens for most types of software systems, testing video games has largely remained a manual activity performed by human testers. This is mostly due to the con…
Evaluating SZZ Implementations Through a Developer-informed Oracle
Giovanni Rosa, Luca Pascarella, Simone Scalabrino +4
The SZZ algorithm for identifying bug-inducing changes has been widely used to evaluate defect prediction techniques and to empirically investigate when, how, and by whom bugs are…
Studying the Usage of Text-To-Text Transfer Transformer to Support Code-Related Tasks
Antonio Mastropaolo, Simone Scalabrino, Nathan Cooper +4
Deep learning (DL) techniques are gaining more and more attention in the software engineering community. They have been used to support several code-related tasks, such as automati…
Why Developers Refactor Source Code: A Mining-based Study
Jevgenija Pantiuchina, Fiorella Zampetti, Simone Scalabrino +4
Refactoring aims at improving code non-functional attributes without modifying its external behavior. Previous studies investigated the motivations behind refactoring by surveying…