Code Analysis
Code Analysis is an automated code review and analysis tool. It enables individual developers, team leads, and managers to ensure that the quality, performance, maintainability, and reliability of their code meets and exceeds their best practice standards.
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Note: This feature is available in the Professional Edition and higher. |
Access to Code Analysis
| Code Editor | Code Analysis is available in the Code Editor, which ensures code quality from the beginning of the development cycle. In the Code Editor, Code Analysis evaluates how well a developer's code adheres to project coding standards and best practices by automatically highlighting errors and suggesting smarter ways to build and test the code. |
| Code Analysis Window | SQL Navigator also provides a dedicated Code Analysis window, where you can perform more detailed analysis, evaluate multiple scripts at the same time, and view a detailed report of the analysis. |
Rules and Rule Sets
Code Analysis compares code against a set of rules (Code Analysis Rules) for best practices. These rules are stored in rule sets (Code Analysis Rule Sets).
The Code Analysis rules and rule sets can be adjusted to suit the requirements of different projects. Regardless of whether developers are responsible for their own code quality or if this needs to be managed centrally, Code Analysis can be adapted to fit either need.
Code Analysis Metrics
Code Analysis uses a variety of metrics to evaluate code, including the following:
- Computational Complexity (Halstead Volume)—Measures a program module's complexity directly from source code, with emphasis on computational complexity. The measures were developed by the late Maurice Halstead as a means of determining a quantitative measure of complexity directly from the operators and operands in the module. Among the earliest software metrics, they are strong indicators of code complexity. Because they are applied to code, they are most often used as a maintenance metric.
- Cyclomatic Complexity (McCabe's)—Cyclomatic complexity is the most widely used member of a class of static software metrics. It measures the number of linearly-independent paths through a program module. This measure provides a single ordinal number that can be compared to the complexity of other programs. It is independent of language and language format.
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Maintainability Index (MI)—Quantitative measurement of an operational system's maintainability is desirable both as an instantaneous measure and as a predictor of maintainability over time. This measurement helps reduce or reverse a system's tendency toward "code entropy" or degraded integrity, and to indicate when it becomes cheaper and/or less risky to rewrite the code than to change it. Applying the MI measurement during software development can help reduce lifecycle costs.
The Code Analysis Report includes detailed descriptions of the code metrics and how they work. For more information, see Code Analysis Window.