GDA has years of scientific software development experience. We make use of industry best-practices and are fully conversant with modern techniques and tools. Our guiding principle is that clients and partners should be able to use our code both as stand-alone products and as a well-integrated component within their own computational systems. We are capable of delivering multi-platform source and binary codes. We can deliver code with run-time environment for diverse metal and virtualized platforms.

Example projects

  • gda-public (our shape analytics suite)
  • Docker
  • Demos (some may be password-protected for individual clients)

Our general practice is to develop proof-of-principle methods, and then work closely with collaborators to integrate those methods within application systems.

We work within and adapt to myriad data-gathering systems and are comfortable with a mixture of open-source and proprietary data, software tools, and hardware systems.

Techniques

  • Deliverables: APIs
  • SDLC: requirements, specification, planning, design, implementation, testing, maintenance
  • Testing: Verification & Validation, unit, integration, component, system
  • Agile frameworks for software development (scrum, kanban)

Tools

  • git and mercurial (distributed version control)
  • parallelized algorithm design, distributed cloud computing, containerization and virtualization, GPU and embedded systems
  • Languages: Python, R, Matlab/Octave, Fortran, C, C++, C#, Java, JavaScript, SageMath/CoCalc
  • Databases: Experience with both relational and noSQL database systems (MySQL, PostgreSQL, MS-SQL, MongoDB, Hadoop)