Big Data for Code

Atlas is a scalable platform for mining and analyzing semantically rich graphs from software. It’s built on two decades of research into solving complex software engineering problems using graphs. Atlas can be used interactively to explore a large dataset derived from software or programmatically to perform sophisticated automatic analysis.

Track record of success:

  • Sophisticated malware detection
  • Automated auditing of safety critical software
  • Application Modernization

Complete Solution

EnSoft provides Atlas, as well as engineering services, to help you build a complete solution for mining relevant information. For example, EnSoft helped a financial services company identify key integration points for an application modernization project.

EnSoft’s expertise extends from building a dataset from your code, setting up a computing environment (big or small), to developing novel graph algorithms to solve your specific problem. For example, EnSoft partnered with Iowa State University to develop a complete malware detection solution for the Defense Advanced Research Projects Agency.


Tailored for Software-derived Datasets

Atlas uses a fast graph database and query engine tailored for a software-derived dataset. In contrast to other big data queries that find patterns within K-degree neighborhoods (e.g. “restaurants my friends’ friends gave 4 or more stars” requires a 3-degree query), software queries can span arbitrary degrees. For example, matching an input variable to an output variable in an embedded controller can easily span nodes that are 100 degrees apart.


Atlas can handle huge datasets in a commodity cluster, but even on a modern desktop you can work with millions of lines of code. 


Atlas was built to work with many programming languages. We provide flag-ship support for Java and C/C++, as well as support for COBOL, Ada, and other industry specific languages. EnSoft can quickly build support for additional languages to meet your project needs.

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