🤖 AI Summary
Detecting design patterns and modeling code refactoring in large-scale, complex software systems remains challenging due to difficulties in representation learning and low computational efficiency. Method: This paper proposes Analytical Software Engineering (ASE), a novel design paradigm. Its core innovations include: (1) a language-agnostic, compact code abstraction—Behavior-Structure Sequence (BSS); (2) an Optimized Design Refactoring (ODR) framework integrating heuristic search with software metric encoding to eliminate iterative computation overhead inherent in conventional refactoring; and (3) a unified design balancing abstraction, tool accessibility, compatibility, and extensibility. Results: Experiments demonstrate that ASE significantly improves both design pattern detection accuracy and refactoring efficiency, validating its effectiveness for maintainability assessment and sustainable optimization. It establishes a new theoretical foundation and a scalable framework for automated analysis of complex software metrics.
📝 Abstract
As modern software systems expand in scale and complexity, the challenges associated with their modeling and formulation grow increasingly intricate. Traditional approaches often fall short in effectively addressing these complexities, particularly in tasks such as design pattern detection for maintenance and assessment, as well as code refactoring for optimization and long-term sustainability. This growing inadequacy underscores the need for a paradigm shift in how such challenges are approached and resolved. This paper presents Analytical Software Engineering (ASE), a novel design paradigm aimed at balancing abstraction, tool accessibility, compatibility, and scalability. ASE enables effective modeling and resolution of complex software engineering problems. The paradigm is evaluated through two frameworks Behavioral-Structural Sequences (BSS) and Optimized Design Refactoring (ODR), both developed in accordance with ASE principles. BSS offers a compact, language-agnostic representation of codebases to facilitate precise design pattern detection. ODR unifies artifact and solution representations to optimize code refactoring via heuristic algorithms while eliminating iterative computational overhead. By providing a structured approach to software design challenges, ASE lays the groundwork for future research in encoding and analyzing complex software metrics.