Most scientific computational and data work can be thought of as a set of high-level steps, and these steps can often be expressed as a workflow. Software tools can help scientists define and execute these workflows, for example, Swift which is both a language and a runtime system. This project could have two parts, depending on the student's interests and experiences. One, focused on scientific applications, will examine how workflows like Swift can be used to help scientific communities that haven't considered generic workflow tools, specifically in astronomy, such as the Large Synoptic Survey Telescope (LSST) and the Square Kilometer Array (SKA). LSST is a new kind of telescope, currently under construction in Chile, designed to conduct a ten-year survey of the dynamic universe. LSST can map the entire visible sky in just a few nights, and images will be immediately analyzed to identify objects that have change or moved: from exploding supernovae on the other side of the Universe to asteroids that might impact the Earth. SKA is a massive, international, multiple radio telescope project, that will provide the highest resolution images in all astronomy. Both projects represent challenging data acquisition and analysis problems, integrating workflows, scientific codes, and advanced data centers. The second, focused on software aspects, will examine how Swift might interact with other open source projects, such as the Apache stack. Interested students should have an interest in high-performance computing, big data computing, and/or distributed computing. They should be proficient in a Linux/Unix software development environment and skilled in the C language. Optional but desirable skills include Java, ANTLR/bison/yacc/lex, sockets, and/or MPI.