Building the Next Generation of Aerospace Data Processing Systems by Reusing Existing Software Components

Abstract

Software is a key ingredient when developing any aerospace system. It is used in embedded electronics, in flight dynamics, in ground and space data processing, and in the current generation of data products. For example, the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center’s Innovative Partnerships Program Office offers licensing opportunities for software and technologies from a variety of areas relevant to the hardware and software requirements of Earth and space science missions and projects: aerospace/aeronautics, computer software, data processing/analysis, electromechanical devices, electronics, manufacturing equipment, mechanical technologies, nanotechnology, optics and photonics, sensor and detector technologies, subassemblies and components, telecommunications and internet, and test and measurement (IPP Office, 2009). Reuse of existing experience and artifacts eliminates having to “reinvent the wheel” and is a key element to achieving progress in many areas of complex aerospace system development. Originally, in the absence of vendor-provided solutions and commercial off-the-shelf software components, many data and information systems were designed and built as custom applications. However, as the practice of systems and applications development has matured, facilitating reuse of software and reusing previously developed software have been recognized as beneficial for meeting the challenges of developing and maintaining complex systems. Some of the challenges commonly faced by system developers can include dealing with very large quantities of data (e.g., terabytes per day), working with a distributed knowledge base, the expense and complexity of required technology infrastructure, and the need for domain-specific knowledge in software development (Samadi et al., 2007). In software development, reuse can assist today’s development teams in various aspects of the system development life cycle, especially when they share common goals (Samadi et al., 2007). The development of new systems can benefit from the efforts that contributed to the development of current and previous generations of systems. Considering the costs of building new systems, and the learning curve that contributes to such costs, leveraging the results of previous system development activities has the potential to reduce system