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Semantic Debugging: Debugging Software Based on Program Meaning Rather Than Syntax


EOI: 10.11242/viva-tech.01.09.04

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Citation

Vaishnavi Pisal, Anojkumar Yadav, Rahul Abhyankar, " Semantic Debugging: Debugging Software Based on Program Meaning Rather Than Syntax", VIVA-IJRI Volume 1, Issue 9, Article 4, pp. 1-6, 2026. Published by Computer Engineering Department, VIVA Institute of Technology, Virar, India.

Abstract

The exponential growth in software complexity, driven by the advent of distributed microservices, cyber-physical systems, and autonomous artificial intelligence, has exposed the fundamental limitations of traditional debugging paradigms. Conventional techniques, primarily predicated on syntax correction and structural analysis, essentially verify whether a program is grammatically correct and whether it executes without crashing. However, they fail to address the increasingly prevalent class of "semantic dissonances"-instances where a program is syntactically valid and executable but fundamentally violates the programmer’s intent or the domain-specific laws governing the system. This research report presents an exhaustive study of Semantic Debugging, an emerging paradigm that shifts the locus of fault localization from code structure to program meaning. By synthesizing diverse fields including Abstract Interpretation, Knowledge Graph generation, Neuro-Symbolic AI, and Formal Methods, semantic debugging aims to formalize and automate the detection of discrepancies between implementation and intent. This paper defines the theoretical underpinnings of semantic debugging, differentiates it from static and dynamic analysis, and proposes a unified Semantic Debugging Architecture (SDA). Furthermore, it explores advanced methodologies such as the ROAD framework for agentic self-correction, BLADE for representation learning in compiler testing, and semantic communication error correction in 6G networks. Through a rigorous analysis of safety-critical applications in automotive systems (ISO 26262) and autonomous infrastructure, we demonstrate that semantic debugging is not merely an enhancement of existing tools but a necessary evolution for the reliability of next-generation software.

Keywords

- Abstract Interpretation, Agentic Workflows, Fault Localization, ISO 26262, Knowledge Graphs, Neuro-Symbolic AI, Self-Healing Systems, Semantic Debugging, 6G Semantic Communication.

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