ATLAS: Automated Tree-based Language Analysis System for C and C++ source programs
Jaid Monwar Chowdhury, Ahmad Farhan Shahriar Chowdhury, Humayra Binte Monwar, Mahmuda Naznin

TL;DR
ATLAS is a Python tool that creates multi-view graph representations of C/C++ code, enabling effective analysis of non-compilable projects and improving test coverage with high accuracy.
Contribution
It introduces a novel, scalable approach for analyzing non-compilable C/C++ code using multi-view graphs, supporting partial analysis and graph optimizations.
Findings
Achieves up to 96.80% CFG success rate and 91.38% DFG success rate.
Increases line coverage by 34.71% and branch coverage by 32.66% in test generation.
Performs comparably or better than KLEE on complex projects.
Abstract
Analyzing non-compilable C/C++ submodules without a resolved build environment remains a critical bottleneck for industrial software evolution. Traditional static analysis tools often fail in these scenarios due to their reliance on successful compilation, while Large Language Models (LLMs) lack the structural context necessary to reason about complex program logic. We introduce ATLAS, a Python-based CLI that generates unified multi-view representations for large-scale C/C++ projects with high accuracy, achieving success rates up to 96.80% for CFGs and 91.38% for DFGs. ATLAS is characterized by: (i) inter-procedural, type-aware analysis across function boundaries; (ii) support for both full and partial analysis of non-compilable projects; (iii) graph optimizations such as variable collapsing and node blacklisting; and (iv) synchronized multi-view graphs that align syntax, execution…
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Taxonomy
TopicsSoftware Engineering Research · Software Testing and Debugging Techniques · Parallel Computing and Optimization Techniques
