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  • AI-based clustering of similar issues in GitHub’s repositories

  • Automatic Identification of Similar Pull-Requests in GitHub’s Repositories Using Machine Learning

  • Automatic Labeling of the Object-oriented Source Code: The Lotus Approach

  • Constructing a software requirements specification and design for electronic IT news magazine system

  • Detecting and Visualizing Implementation Feature Interactions in Extracted Core Assets of Software Product Line

  • DETECTING COMMONALITY AND VARIABILITY IN USE-CASE DIAGRAM VARIANTS

  • Feature-based insight for forks in social coding platforms

  • Leveraging a combination of machine learning and formal concept analysis to locate the implementation of features in software variants

  • ML-Augmented Automation for Recovering Links Between Pull-Requests and Issues on GitHub

  • Naming the Identified Feature Implementation Blocks from Software Source Code

  • Naming the Identified Feature Implementation Blocks from Software Source Code

  • Object-oriented Software Documentation

  • PI-Link: A Ground-Truth Dataset of Links Between Pull-Requests and Issues in GitHub

  • Predicting Quality Medical Drug Data Towards Meaningful Data using Machine Learning

  • Requirements Traceability: Recovering and Visualizing Traceability Links Between Requirements and Source Code of Object-oriented Software Systems

  • ScaMaha: A Tool for Parsing, Analyzing, and Visualizing Object-Oriented Software Systems

  • Smart Cities: Definitions, Architectures, Technologies, Life Cycle, Domains, Challenges, Opportunities, and the Case of Amman

  • SoftCloud: A Tool for Visualizing Software Artifacts as Tag Clouds

  • Software evolution understanding: Automatic extraction of software identifiers map for object-oriented software systems

  • Tag Clouds for Object-Oriented Source Code Visualization

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