55 results on '"A, Di Nucci"'
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2. Using Large Language Models to Support Software Engineering Documentation in Waterfall Life Cycles: Are We There Yet?
3. Integrating Data Quality in Industrial Big Data Architectures: An Action Design Research Study.
4. Toward a Search-Based Approach to Support the Design of Security Tests for Malicious Network Traffic.
5. Data Quality Assessment in the Wild: Findings from GitHub.
6. Detecting Security Fixes in Open-Source Repositories using Static Code Analyzers.
7. Architectural Design Decisions for Self-Serve Data Platforms in Data Meshes.
8. Unmasking Data Secrets: An Empirical Investigation into Data Smells and Their Impact on Data Quality.
9. Data Mesh Architecture: From Theory to Practice.
10. CarPatch: A Synthetic Benchmark for Radiance Field Evaluation on Vehicle Components.
11. ADAS Verification in Co-Simulation: Towards a Meta-Model for Defining Test Scenarios.
12. Defuse: A Data Annotator and Model Builder for Software Defect Prediction.
13. Towards Quantum-algorithms-as-a-service.
14. Exploiting dynamic analysis for architectural smell detection: a preliminary study.
15. A Multivocal Literature Review of MLOps Tools and Features.
16. A preliminary evaluation on the relationship among architectural and test smells.
17. Toward Automated Exploit Generation for Known Vulnerabilities in Open-Source Libraries.
18. A Delta-Debugging Approach to Assessing the Resilience of Actor Programs through Run-time Test Perturbations.
19. Counterterrorism for Cyber-Physical Spaces: A Computer Vision Approach.
20. Refactoring Android-specific Energy Smells: A Plugin for Android Studio.
21. DeepIaC: deep learning-based linguistic anti-pattern detection in IaC.
22. Singling the odd ones out: a novelty detection approach to find defects in infrastructure-as-code.
23. DevOps and Quality Management in Serverless Computing: The RADON Approach.
24. The Making of Accessible Android Applications: An Empirical Study on the State of the Practice.
25. Cross-project just-in-time bug prediction for mobile apps: an empirical assessment.
26. Comparing heuristic and machine learning approaches for metric-based code smell detection.
27. Assessing diffusion and perception of test smells in scala projects.
28. Mining Patterns in Source Code Using Tree Mining Algorithms.
29. On the role of data balancing for machine learning-based code smell detection.
30. SoCRATES: Scala radar for test smells.
31. Mining Scala Framework Extensions for Recommendation Patterns.
32. Evaluating the Adaptive Selection of Classifiers for Cross-Project Bug Prediction.
33. Self-reported activities of Android developers.
34. Do developers update third-party libraries in mobile apps?
35. Mining Extension Point Patterns in Scala.
36. A graph-based dataset of commit history of real-world Android apps.
37. OCELOT: a search-based test-data generation tool for C.
38. Methods and Tools for Focusing and Prioritizing the Testing Effort.
39. Omniscient DevOps Analytics.
40. The role of meta-learners in the adaptive selection of classifiers.
41. Detecting code smells using machine learning techniques: Are we there yet?
42. PETrA: a software-based tool for estimating the energy profile of Android applications.
43. Software-based energy profiling of Android apps: Simple, efficient and reliable?
44. Lightweight detection of Android-specific code smells: The aDoctor project.
45. A Language-Parametric Modular Framework for Mining Idiomatic Code Patterns.
46. On the diffusion of test smells in automatically generated test code: an empirical study.
47. Search-Based Testing of Procedural Programs: Iterative Single-Target or Multi-target Approach?
48. Landfill: An Open Dataset of Code Smells with Public Evaluation.
49. Hypervolume-Based Search for Test Case Prioritization.
50. On the role of developer's scattered changes in bug prediction.
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