Learn about the initial process CodeQL follows when creating a database for code analysis. Discover how it extracts a relational representation of source files to enable efficient querying and analysis of your codebase using GitHub Advanced Security.
Table of Contents
Question
What does CodeQL first do when you’re creating a database?
A. Analyzes both compiled languages and interpreted languages.
B. Extracts a single relational representation of each source file.
C. Converts results produced during query execution into a meaningful form.
Answer
B. Extracts a single relational representation of each source file.
Explanation
For database creation, CodeQL first extracts a single relational representation of each source file in the codebase.
When creating a CodeQL database, the first step is to extract a single relational representation of each source file in the codebase. This process is crucial for enabling efficient analysis and querying of the code using CodeQL.
Here’s a detailed explanation of what happens during this initial step:
- Source Code Extraction: CodeQL starts by reading and parsing the source code files of the target codebase. It supports a wide range of programming languages, including both compiled languages (such as C++, Java, and Go) and interpreted languages (such as JavaScript and Python).
- Abstract Syntax Tree (AST) Generation: For each source file, CodeQL generates an abstract syntax tree (AST). The AST is a structured representation of the code that captures its syntactic structure and the relationships between different code elements (such as classes, functions, and variables).
- Relational Representation: CodeQL then transforms the AST into a relational representation. This involves extracting relevant information from the AST and storing it in a set of tables that represent different aspects of the code. For example, there might be tables for classes, methods, variables, and their relationships (such as method calls and variable assignments).
- Normalization and Optimization: During the extraction process, CodeQL normalizes and optimizes the relational representation to ensure consistency and efficiency. This may involve resolving references, handling language-specific idioms, and applying various optimizations to improve query performance.
- Database Creation: Finally, CodeQL combines the relational representations of all the source files into a single CodeQL database. This database serves as the foundation for subsequent analysis and querying using CodeQL queries.
By extracting a single relational representation of each source file, CodeQL creates a unified and structured view of the entire codebase. This enables developers and security researchers to write expressive queries to analyze the code for various purposes, such as identifying security vulnerabilities, detecting code quality issues, and understanding the structure and behavior of the codebase.
It’s important to note that the analysis of both compiled languages and interpreted languages, as well as the conversion of query results into a meaningful form, are separate steps that occur later in the CodeQL analysis process. The initial focus is on extracting the relational representation of the source files to build the foundation for subsequent analysis tasks.
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