Evaluation of Novel Approaches to Software Engineering 18th International Conference, ENASE 2023, Prague, Czech Republic, April 24–25, 2023, Revised Selected Papers /
This book constitutes the refereed post-conference proceedings of the 18th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2023, held in Prague, Czech Republic, during April 24–25, 2023. The 15 revised full papers presented in these proceedings were carefull...
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| Autor corporatiu: | |
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| Altres autors: | , , |
| Format: | Electrònic eBook |
| Idioma: | anglès |
| Publicat: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
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| Edició: | 1st ed. 2024. |
| Col·lecció: | Communications in Computer and Information Science,
2028 |
| Matèries: | |
| Accés en línia: | https://doi.org/10.1007/978-3-031-64182-4 |
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Taula de continguts:
- 1 Leveraging Digital Trace Data to Investigate and Support Human-Centered Work Processes
- 2 What Should Be in a Persona for Use in Requirements Engineering
- 3 Impact Analysis of Disruptions on Composite Resources
- 4 Requirements Elicitation in the Age of AI: A Tool’s Multi-System Journey
- 5 A Deep Contextual Product Recommender System for SO-DSPL Framework
- 6 Beyond the Systematic: Forecasting Importance and Emergence of Research Areas in Applications of Software Traceability Using NLP
- 7 A Method for Model-Driven IoT Application Development
- 8 Operationalizing Decision Tables: A Step-by-Step Framework for Efficient Software Product Line Customization
- 9 Singleton and Factory Design Patterns Detection Based on Features and Machine Learning
- 10 Future Vision of Dynamic Certification Schemes for Autonomous Systems
- 11 Advancing Code Smell Detection: Live Global Data Detection and Data Clump Test Cases
- 12 Dynamic Data-Flow Analysis With Dacite: Evaluating an Integrated Data-Flow Visualization Approach
- 13 Enhancing Software Defect Prediction: Exploring the Predictive Power of Two Data Flow Metrics
- 14 Adaptive Strategies Metric Suite
- 15 Enhancing Collaboration and Agility in Data-Centric AI Projects.