From Separate Compilation to Sound Language Composition

2026-02-03

AI Summary

This work addresses the challenge of undefined attribute accesses introduced by attribute grammar extensions in language frameworks that support modular, separate compilation—issues that compromise artifact reuse and trigger runtime errors. To mitigate this, we present nlgcheck, a static analysis tool designed for the Neverlang language workbench that, for the first time, enables static soundness checking of attribute grammar extensions in a separately compilable language composition system. Leveraging data-flow analysis, nlgcheck verifies the legality of attribute accesses at compile time, thereby reconciling modularity, flexibility, and static safety. Experimental evaluation demonstrates that nlgcheck effectively enhances system robustness while incurring performance overhead that remains acceptable for typical development workflows.

Technology Category

• Natural Language Processing: Safety and Robustness
• Knowledge Representation and Reasoning: Knowledge Representation Languages
• Constraint Satisfaction and Optimization: Satisfiability Modulo Theories

Application Category

• Search and Retrieval-Augmented AI: Multilingual and cross-lingual Web search
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions

Abstract

The development of programming languages involves complex theoretical and practical challenges, particularly when addressing modularity and reusability through language extensions. While language workbenches aim to enable modular development under the constraints of the language extension problem, one critical constraint -- separate compilation -- is often relaxed due to its complexity. However, this relaxation undermines artifact reusability and integration with common dependency systems. A key difficulty under separate compilation arises from managing attribute grammars, as extensions may introduce new attributes that invalidate previously generated abstract syntax tree structures. Existing approaches, such as the use of dynamic maps in the Neverlang workbench, favor flexibility at the cost of compile-time correctness, leading to potential runtime errors due to undefined attributes. This work addresses this issue by introducing nlgcheck, a theoretically sound static analysis tool based on data-flow analysis for the Neverlang language workbench. nlgcheck detects potential runtime errors -- such as undefined attribute accesses -- at compile time, preserving separate compilation while maintaining strong static correctness guarantees. Experimental evaluation using mutation testing on Neverlang-based projects demonstrates that nlgcheck effectively enhances robustness without sacrificing modularity or flexibility and with a level of performance that does not impede its adoption in daily development activities.

Problem

• separate compilation
• language composition
• attribute grammars
• static correctness
• undefined attributes

Innovation

• separate compilation
• static analysis
• attribute grammars
• language workbench
• data-flow analysis