Static Analysis Tool for Creating an Inventory of your Source Code
Analyze your source code with RapidScan to make an informed decision
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Run RapidScan to analyze your source code for free.
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Get a free static code analysis report with a detailed inventory of your source code.
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Understand your options for successfully modernizing your source code.
Over the years, source code piles up in repositories and servers and given sufficient changes and branches, it can be difficult or impossible to understand what you have.
You can't deal with what you have until you know what you have and that is where our RapidScan source code analysis tool comes in.
A full listing of every file found in the folder tree, including all subfolders
Known binary files are identified and the number of bytes of each is recorded
Known source file extensions are used to categorize source code files (like C#, Python, VB.NET, and more).
Each file gets a report of the total lines of code and is associated with its programming language.
Unknown ASCII files are reported with a line count, separating blank lines from non-blank lines.
Unknown file types over a given size are assumed to be binary
RapidScan recognizes files used by the following programming languages:
Visual Basic 6.0, .NET, C#, VB.NET
ASP, ASP.NET
C/C++
Delphi/Pascal
Java
JavaScript, JSON, TypeScript
PHP
PowerBuilder
Python
SQL
Teradata BTEQ
Informix 4GL
XAML
XML, HTML
Scan your code and get analysis reports like these:
RapidScan is simple to use
Just identify a root folder and go. It will walk the folder tree, collecting metadata about your source code for analysis.
The output is in the form of easy-to-read CSV files. In addition, the output is compatible with data visualization tools like Microsoft Excel, Tableau, Power BI, and others.
Submit the metadata to receive a free Excel template to provide more data on your code. Plus, our migration engineers are ready to help you interpret the results. No source code is uploaded or captured.
A quick phone call to review your data can provide valuable insights into what workloads can be made cloud-ready quickly, and which might need additional effort.
