Authors :
Vijay V.; K. Krishna Veni; Divya. S.
Volume/Issue :
Volume 11 - 2026, Issue 3 - March
Google Scholar :
https://tinyurl.com/4nf74h2b
Scribd :
https://tinyurl.com/3w7tj7v2
DOI :
https://doi.org/10.38124/ijisrt/26mar1929
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Code quality assurance is a fundamental requirement in modern software engineering to ensure maintainability,
security, and reliability. Traditional manual review methods are time-consuming and inconsistent, while enterprise-grade
static analysis tools such as SonarQube impose infrastructure complexity and licensing costs. This paper presents the design
and implementation of the Rapid Code Quality Analyzer (RCQA), a lightweight, web-based static analysis system designed
for academic institutions and small development teams.
RCQA supports six programming languages—Python, Java, JavaScript, TypeScript, C, and C++—using Abstract
Syntax Tree (AST) analysis for Python and regex-based heuristic analysis for other languages. The system evaluates source
code using metrics including Cyclomatic Complexity, Cognitive Complexity, Halstead Effort, Maintainability Index, Lines
of Code, and security vulnerability detection. A weighted scoring model produces a unified quality score (0–100), classifying
code from Enterprise Ready to High Risk.
The platform is implemented using FastAPI, SQLite, SQLAlchemy, JWT authentication, bcrypt hashing, and a
responsive HTML/CSS/JavaScript frontend with Chart.js visualization. Experimental evaluation demonstrates accurate
detection of complexity and security issues with efficient performance for typical academic-scale codebases. The study
concludes that effective multi-language static analysis can be delivered using open-source technologies without enterprise
overhead.
Keywords :
Static Code Analysis, Software Quality Metrics, Cyclomatic Complexity, Maintainability Index, FastAPI, Secure Coding, Multi-language Analysis.
References :
- McCabe, T. J. (1976). A Complexity Measure. IEEE Transactions on Software Engineering.
- Halstead, M. H. (1977). Elements of Software Science.
- Oman, P., & Hagemeister, J. (1992). Metrics for Assessing a Software System’s Maintainability.
- FastAPI Documentation.
- SQLAlchemy Documentation.
- OWASP Top 10 Security Risks.
Code quality assurance is a fundamental requirement in modern software engineering to ensure maintainability,
security, and reliability. Traditional manual review methods are time-consuming and inconsistent, while enterprise-grade
static analysis tools such as SonarQube impose infrastructure complexity and licensing costs. This paper presents the design
and implementation of the Rapid Code Quality Analyzer (RCQA), a lightweight, web-based static analysis system designed
for academic institutions and small development teams.
RCQA supports six programming languages—Python, Java, JavaScript, TypeScript, C, and C++—using Abstract
Syntax Tree (AST) analysis for Python and regex-based heuristic analysis for other languages. The system evaluates source
code using metrics including Cyclomatic Complexity, Cognitive Complexity, Halstead Effort, Maintainability Index, Lines
of Code, and security vulnerability detection. A weighted scoring model produces a unified quality score (0–100), classifying
code from Enterprise Ready to High Risk.
The platform is implemented using FastAPI, SQLite, SQLAlchemy, JWT authentication, bcrypt hashing, and a
responsive HTML/CSS/JavaScript frontend with Chart.js visualization. Experimental evaluation demonstrates accurate
detection of complexity and security issues with efficient performance for typical academic-scale codebases. The study
concludes that effective multi-language static analysis can be delivered using open-source technologies without enterprise
overhead.
Keywords :
Static Code Analysis, Software Quality Metrics, Cyclomatic Complexity, Maintainability Index, FastAPI, Secure Coding, Multi-language Analysis.
