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Dario Di Nucci
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- affiliation: University of Salerno, Italy
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2020 – today
- 2025
- [j28]Abel Goedegebuure
, Indika Kumara
Data Mesh: A Systematic Gray Literature Review. ACM Comput. Surv. 57(1): 11:1-11:36 (2025) - 2024
- [j27]Valeria Pontillo
Machine learning-based test smell detection. Empir. Softw. Eng. 29(2): 55 (2024) - [j26]Manuel De Stefano
An empirical study into the effects of transpilation on quantum circuit smells. Empir. Softw. Eng. 29(3): 61 (2024) - [j25]Manuel De Stefano
The quantum frontier of software engineering: A systematic mapping study. Inf. Softw. Technol. 175: 107525 (2024) - [j24]Gilberto Recupito, Fabiano Pecorelli, Gemma Catolino, Valentina Lenarduzzi, Davide Taibi
Technical debt in AI-enabled systems: On the prevalence, severity, impact, and management strategies for code and architecture. J. Syst. Softw. 216: 112151 (2024) - [j23]Stefan W. Driessen
SolAR: Automated test-suite generation for solidity smart contracts. Sci. Comput. Program. 232: 103036 (2024) - [j22]Stefano Dalla Palma
"Through the looking-glass ..." An empirical study on blob infrastructure blueprints in the Topology and Orchestration Specification for Cloud Applications. J. Softw. Evol. Process. 36(4) (2024) - [j21]Daan Hommersom
Automated Mapping of Vulnerability Advisories onto their Fix Commits in Open Source Repositories. ACM Trans. Softw. Eng. Methodol. 33(5): 134:1-134:28 (2024) - [c49]Gilberto Recupito
Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality. CAIN 2024: 53-63 - [c48]Ipek Ustunboyacioglu
Data Quality Assessment in the Wild: Findings from GitHub. EASE 2024: 120-129 - [c47]Therese Fehrer
Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers. EASE 2024: 429-432 - [c46]Davide La Gamba
Toward a Search-Based Approach to Support the Design of Security Tests for Malicious Network Traffic. EASE 2024: 624-628 - [c45]Ipek Ustunboyacioglu, Indika Kumara
Integrating Data Quality in Industrial Big Data Architectures: An Action Design Research Study. ECSA 2024: 3-19 - [c44]Tom van Eijk, Indika Kumara, Dario Di Nucci, Damian Andrew Tamburri, Willem-Jan van den Heuvel:
Architectural Design Decisions for Self-Serve Data Platforms in Data Meshes. ICSA 2024: 135-145 - [c43]Indika Kumara, Stefan Driessen, Tom van Eijk, Dario Di Nucci, Damian Andrew Tamburri, Willem-Jan van den Heuvel:
Data Mesh Architecture: From Theory to Practice. ICSA-C 2024: 375-376 - [c42]Antonio Della Porta, Vincenzo De Martino, Gilberto Recupito, Carmine Iemmino, Gemma Catolino, Dario Di Nucci, Fabio Palomba:
Using Large Language Models to Support Software Engineering Documentation in Waterfall Life Cycles: Are We There Yet? Ital-IA 2024: 42-47 - [c41]Sabato Nocera
Do Static Analysis Tools Improve Awareness and Attitude Toward Secure Software Development? QUATIC 2024: 399-407 - [i12]Tom van Eijk, Indika Kumara, Dario Di Nucci
Architectural Design Decisions for Self-Serve Data Platforms in Data Meshes. CoRR abs/2402.04681 (2024) - [i11]Gilberto Recupito, Giammaria Giordano, Filomena Ferrucci, Dario Di Nucci
When Code Smells Meet ML: On the Lifecycle of ML-specific Code Smells in ML-enabled Systems. CoRR abs/2403.08311 (2024) - 2023
- [j20]Camilo Velázquez-Rodríguez
A text classification approach to API type resolution for incomplete code snippets. Sci. Comput. Program. 227: 102941 (2023) - [j19]Stefano Dalla Palma, Gemma Catolino
Go Serverless With RADON! A Practical DevOps Experience Report. IEEE Softw. 40(2): 80-89 (2023) - [c40]Francesco Basciani, Vittorio Cortellessa, Sergio Di Martino, Dario Di Nucci
ADAS Verification in Co-Simulation: Towards a Meta-Model for Defining Test Scenarios. ICSTW 2023: 28-35 - [e3]Andrea De Lucia, Dario Di Nucci, Valeria Pontillo, Gilberto Recupito:
Proceedings of the 15th Seminar on Advanced Techniques & Tools for Software Evolution, University of Salerno, Computer Science Department - Fisciano (Salerno, Italy), June 12 to 14, 2023. CEUR Workshop Proceedings 3483, CEUR-WS.org 2023 [contents] - [i10]Abel Goedegebuure, Indika Kumara, Stefan Driessen, Dario Di Nucci
Data Mesh: a Systematic Gray Literature Review. CoRR abs/2304.01062 (2023) - [i9]Manuel De Stefano, Fabiano Pecorelli, Dario Di Nucci, Fabio Palomba, Andrea De Lucia:
The Quantum Frontier of Software Engineering: A Systematic Mapping Study. CoRR abs/2305.19683 (2023) - 2022
- [j18]Marianna Di Gregorio, Dario Di Nucci
The making of accessible Android applications: an empirical study on the state of the practice. Empir. Softw. Eng. 27(6): 145 (2022) - [j17]Nemania Borovits, Indika Kumara
FindICI: Using machine learning to detect linguistic inconsistencies between code and natural language descriptions in infrastructure-as-code. Empir. Softw. Eng. 27(7): 178 (2022) - [j16]Manuel De Stefano
Software engineering for quantum programming: How far are we? J. Syst. Softw. 190: 111326 (2022) - [j15]Eleni Constantinou, Dario Di Nucci
Special Issue on Software Health of Software Ecosystems. Sci. Comput. Program. 218: 102805 (2022) - [j14]Stefano Dalla Palma
Within-Project Defect Prediction of Infrastructure-as-Code Using Product and Process Metrics. IEEE Trans. Software Eng. 48(6): 2086-2104 (2022) - [c39]Gilberto Recupito
A Multivocal Literature Review of MLOps Tools and Features. SEAA 2022: 84-91 - [c38]Ilaria Pigazzini, Dario Di Nucci
Exploiting dynamic analysis for architectural smell detection: a preliminary study. SEAA 2022: 282-289 - [c37]Stefano Dalla Palma, Dario Di Nucci
Defuse: A Data Annotator and Model Builder for Software Defect Prediction. ICSME 2022: 479-483 - [c36]Manuel De Stefano, Dario Di Nucci
Towards Quantum-algorithms-as-a-service. QP4SE@ESEC/SIGSOFT FSE 2022: 7-10 - [c35]Manuel De Stefano, Fabiano Pecorelli, Dario Di Nucci
A preliminary evaluation on the relationship among architectural and test smells. SCAM 2022: 66-70 - [e2]Gemma Catolino, Dario Di Nucci, Damian A. Tamburri:
Proceedings of the 20th Belgium-Netherlands Software Evolution Workshop, Virtual Event / 's-Hertogenbosch, The Netherlands, December 7-8, 2021. CEUR Workshop Proceedings 3071, CEUR-WS.org 2022 [contents] - [i8]Manuel De Stefano, Fabiano Pecorelli, Dario Di Nucci
Software Engineering for Quantum Programming: How Far Are We? CoRR abs/2203.16969 (2022) - [i7]Valeria Pontillo, Dario Amoroso d'Aragona, Fabiano Pecorelli
Machine Learning-Based Test Smell Detection. CoRR abs/2208.07574 (2022) - 2021
- [j13]Indika Kumara, Martin Garriga, Angel Urbano Romeu, Dario Di Nucci
The do's and don'ts of infrastructure code: A systematic gray literature review. Inf. Softw. Technol. 137: 106593 (2021) - [j12]Maarten Vandercammen
Prioritising Server Bugs via Inter-process Concolic Testing. Art Sci. Eng. Program. 5(2): 5 (2021) - [j11]Fabiano Pecorelli
Adaptive selection of classifiers for bug prediction: A large-scale empirical analysis of its performances and a benchmark study. Sci. Comput. Program. 205: 102611 (2021) - [c34]Emanuele Iannone
Toward Automated Exploit Generation for Known Vulnerabilities in Open-Source Libraries. ICPC 2021: 396-400 - [i6]Stefan Driessen
AGSolT: a Tool for Automated Test-Case Generation for Solidity Smart Contracts. CoRR abs/2102.08864 (2021) - [i5]Therese Fehrer, Rocío Cabrera Lozoya, Antonino Sabetta, Dario Di Nucci, Damian A. Tamburri:
Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers. CoRR abs/2105.03346 (2021) - [i4]Stefano Dalla Palma, Dario Di Nucci, Damian A. Tamburri:
RepoMiner: a Language-agnostic Python Framework to Mine Software Repositories for Defect Prediction. CoRR abs/2111.11807 (2021) - 2020
- [j10]Pasquale Salza
Third-party libraries in mobile apps. Empir. Softw. Eng. 25(3): 2341-2377 (2020) - [j9]Fabiano Pecorelli
A large empirical assessment of the role of data balancing in machine-learning-based code smell detection. J. Syst. Softw. 169: 110693 (2020) - [j8]Stefano Dalla Palma
Toward a catalog of software quality metrics for infrastructure code. J. Syst. Softw. 170: 110726 (2020) - [j7]Stefano Dalla Palma
AnsibleMetrics: A Python library for measuring Infrastructure-as-Code blueprints in Ansible. SoftwareX 12: 100633 (2020) - [j6]Dario Di Nucci
A Test Case Prioritization Genetic Algorithm Guided by the Hypervolume Indicator. IEEE Trans. Software Eng. 46(6): 674-696 (2020) - [c33]Giuseppe Cascavilla
Counterterrorism for Cyber-Physical Spaces: A Computer Vision Approach. AVI 2020: 52:1-52:5 - [c32]Stefano Dalla Palma
DevOps and Quality Management in Serverless Computing: The RADON Approach. ESOCC Workshops 2020: 155-160 - [c31]Jonas De Bleser, Dario Di Nucci
A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations. AST@ICSE 2020: 21-30 - [c30]Marianna Di Gregorio, Dario Di Nucci
The Making of Accessible Android Applications: An Empirical Study on the State of the Practice. ICSME 2020: 857-861 - [c29]Emanuele Iannone
Refactoring Android-specific Energy Smells: A Plugin for Android Studio. ICPC 2020: 451-455 - [c28]Nemania Borovits
DeepIaC: deep learning-based linguistic anti-pattern detection in IaC. MaLTeSQuE@ESEC/SIGSOFT FSE 2020: 7-12 - [c27]Stefano Dalla Palma
Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code. MaLTeSQuE@ESEC/SIGSOFT FSE 2020: 31-36 - [e1]Dario Di Nucci, Coen De Roover:
Proceedings of the 18th Belgium-Netherlands Software Evolution Workshop, Brussels, Belgium, November 28th to 29th, 2019. CEUR Workshop Proceedings 2605, CEUR-WS.org 2020 [contents] - [i3]Stefano Dalla Palma, Dario Di Nucci, Fabio Palomba, Damian A. Tamburri:
Towards a Catalogue of Software Quality Metrics for Infrastructure Code. CoRR abs/2005.13474 (2020) - [i2]Nemania Borovits, Indika Kumara, Parvathy Krishnan, Stefano Dalla Palma, Dario Di Nucci, Fabio Palomba, Damian A. Tamburri, Willem-Jan van den Heuvel:
DeepIaC: Deep Learning-Based Linguistic Anti-pattern Detection in IaC. CoRR abs/2009.10801 (2020) - [i1]Maarten Vandercammen, Laurent Christophe, Dario Di Nucci, Wolfgang De Meuter, Coen De Roover:
Prioritising Server Bugs via Inter-process Concolic Testing. CoRR abs/2010.16303 (2020)
2010 – 2019
- 2019
- [j5]Fabio Palomba
On the impact of code smells on the energy consumption of mobile applications. Inf. Softw. Technol. 105: 43-55 (2019) - [j4]Giovanni Grano
Scented since the beginning: On the diffuseness of test smells in automatically generated test code. J. Syst. Softw. 156: 312-327 (2019) - [c26]Hoang-Son Pham
Mining Patterns in Source Code Using Tree Mining Algorithms. DS 2019: 471-480 - [c25]Gemma Catolino, Dario Di Nucci
Cross-project just-in-time bug prediction for mobile apps: an empirical assessment. MOBILESoft@ICSE 2019: 99-110 - [c24]Fabiano Pecorelli
Comparing heuristic and machine learning approaches for metric-based code smell detection. ICPC 2019: 93-104 - [c23]Jonas De Bleser, Dario Di Nucci
Assessing diffusion and perception of test smells in scala projects. MSR 2019: 457-467 - [c22]Dario Di Nucci, Hoang-Son Pham, Johan Fabry, Coen De Roover, Kim Mens, Tim Molderez, Siegfried Nijssen, Vadim Zaytsev:
A Language-Parametric Modular Framework for Mining Idiomatic Code Patterns. SATToSE 2019 - [c21]Jonas De Bleser, Dario Di Nucci
SoCRATES: Scala radar for test smells. SCALA@ECOOP 2019: 22-26 - [c20]Fabiano Pecorelli
On the role of data balancing for machine learning-based code smell detection. MaLTeSQuE@ESEC/SIGSOFT FSE 2019: 19-24 - [c19]Yunior Pacheco
Mining Scala Framework Extensions for Recommendation Patterns. SANER 2019: 514-523 - [d1]Giovanni Grano
Online Appendix - Scented Since the Beginning: On the Diffuseness of Test Smells in Automatically Generated Test Code. Zenodo, 2019 - 2018
- [j3]Dario Di Nucci
A Developer Centered Bug Prediction Model. IEEE Trans. Software Eng. 44(1): 5-24 (2018) - [c18]Yunior Pacheco, Jonas De Bleser, Tim Molderez, Dario Di Nucci, Wolfgang De Meuter, Coen De Roover:
Mining Extension Point Patterns in Scala. BENEVOL 2018: 16-20 - [c17]Dario Di Nucci
Evaluating the Adaptive Selection of Classifiers for Cross-Project Bug Prediction. RAISE@ICSE 2018: 48-54 - [c16]Luca Pascarella
Self-reported activities of Android developers. MOBILESoft@ICSE 2018: 144-155 - [c15]Dario Di Nucci
Methods and Tools for Focusing and Prioritizing the Testing Effort. ICSME 2018: 722-726 - [c14]Pasquale Salza
Do developers update third-party libraries in mobile apps? ICPC 2018: 255-265 - [c13]Simone Scalabrino
OCELOT: a search-based test-data generation tool for C. ASE 2018: 868-871 - [c12]Damian Andrew Tamburri
Omniscient DevOps Analytics. DEVOPS 2018: 48-59 - [c11]Franz-Xaver Geiger, Ivano Malavolta
A graph-based dataset of commit history of real-world Android apps. MSR 2018: 30-33 - [c10]Dario Di Nucci
The role of meta-learners in the adaptive selection of classifiers. MaLTeSQuE 2018: 7-12 - [c9]Dario Di Nucci
Detecting code smells using machine learning techniques: Are we there yet? SANER 2018: 612-621 - 2017
- [j2]Dario Di Nucci
Dynamic Selection of Classifiers in Bug Prediction: An Adaptive Method. IEEE Trans. Emerg. Top. Comput. Intell. 1(3): 202-212 (2017) - [c8]Dario Di Nucci
PETrA: a software-based tool for estimating the energy profile of Android applications. ICSE (Companion Volume) 2017: 3-6 - [c7]Dario Di Nucci
Software-based energy profiling of Android apps: Simple, efficient and reliable? SANER 2017: 103-114 - [c6]Fabio Palomba
Lightweight detection of Android-specific code smells: The aDoctor project. SANER 2017: 487-491 - 2016
- [c5]Fabio Palomba
On the diffusion of test smells in automatically generated test code: an empirical study. SBST@ICSE 2016: 5-14 - [c4]Simone Scalabrino
Search-Based Testing of Procedural Programs: Iterative Single-Target or Multi-target Approach? SSBSE 2016: 64-79 - 2015
- [j1]Dario Di Nucci
ICSE 2015 SIGSOFT CAPS Report. ACM SIGSOFT Softw. Eng. Notes 40(4): 22 (2015) - [c3]Dario Di Nucci
On the role of developer's scattered changes in bug prediction. ICSME 2015: 241-250 - [c2]Fabio Palomba
Landfill: An Open Dataset of Code Smells with Public Evaluation. MSR 2015: 482-485 - [c1]Dario Di Nucci
Hypervolume-Based Search for Test Case Prioritization. SSBSE 2015: 157-172
Coauthor Index
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last updated on 2024-12-23 19:32 CET by the dblp team
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