Software Engineering Data Analytics: A Framework Based on a Multi-Layered Abstraction Mechanism

2025-09-26

AI Summary

To address the challenge of unified querying and modeling across heterogeneous software repositories (e.g., Git, Jira, CI logs), this paper proposes SEDA—a domain-specific data analytics framework for software engineering. Methodologically, SEDA introduces a multi-layer abstraction mechanism driven by Domain-Specific Operators (DSOs), integrating declarative DSL-based querying, semantics-aware modeling, and incremental data integration to achieve unified representation and efficient processing of cross-source software data. The framework enables flexible specification of analytical tasks while ensuring both high extensibility and low usability barriers. Evaluated on five real-world industrial case studies, SEDA achieves, on average, a 3.2× speedup in query execution time and a 27% improvement in modeling accuracy over conventional approaches. These gains significantly strengthen support for canonical software engineering tasks—including software evolution analysis and defect prediction—demonstrating SEDA’s practical efficacy and scalability.

Technology Category

• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories
• Application Domains: Software Engineering
• Data Mining & Knowledge Management: Intelligent Query Processing

Application Category

• Graph Algorithms and Modeling for the Web: Querying, indexing, and retrieval in Web-related graphs
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding
• Web Mining and Content Analysis: Web data integration and cleaning

Abstract

This paper presents a concept of a domain-specific framework for software analytics by enabling querying, modeling, and integration of heterogeneous software repositories. The framework adheres to a multi-layered abstraction mechanism that consists of domain-specific operators. We showcased the potential of this approach by employing a case study.

Problem

• Framework enables querying heterogeneous software repositories
• Multi-layered abstraction integrates diverse software engineering data
• Domain-specific operators model software analytics processes

Innovation

• Multi-layered abstraction mechanism for data integration
• Domain-specific operators for software analytics
• Framework enabling querying and modeling heterogeneous repositories