This workshop is concerned with identifying and understanding the unique aspects of software development for Computational Science & Engineering (CSE) applications. Specifically, we are focused on: Scientific or engineering software applications, where the focus is on directly solving scientific or engineering problems. These applications range from large, parallel models/simulations of the physical world using high performance computing systems to smaller scale simulations developed by a single scientist or engineer on a desktop machine. Applications that support scientific endeavors. Such applications include, but are not limited to, systems for managing and/or manipulating large amounts of data and systems that provide infrastructure for scientific or engineering applications. Despite its importance, CSE has historically attracted little attention from the software engineering (SE) community. Indeed, the development of CSE software differs significantly from the development of business information systems, from which many of the SE best practices, tools and techniques have been drawn. These differences include, for example: CSE projects are often exploring unknown science, making it difficult to determine a concrete set of requirements a priori. For the same reason, a test oracle may not exist (for example, the physical data needed to validate a simulation may not exist). The lack of an oracle clearly poses challenges to the development of a testing strategy. A CSE project’s lifecycle is likely to differ from traditional models. For example, in one workflow (“lone researcher”), a single scientist develops software to test a hypothesis and then discards the software. As another example, some projects can last ten years or more and are in constant development throughout. CS&E applications often require more computing resources than are available on a typical workstation. Existing solutions for providing more computational resources (e.g., clusters, supercomputers, grids) can be difficult to use, resulting in additional software engineering challenges. Many CSE software developers are experts – often with a PhD in the underlying scientific or engineering domain – but have little formal training in SE tools and techniques. It’s not uncommon for a single scientist to take on the role of software developer and rely solely on the internet to acquire relevant software development knowledge. New researchers are coming into this line of research and are often unaware of each other’s work. There is no one preferred journal for publication or other readily found source for researchers with this common interest. So this meeting is an important focal point. We intend to spread a wide net, encouraging attendance from researchers in the many areas of computational science as well as software engineering, and educators teaching computer science/software engineering to computational science students. One of the main objectives is to provide an opportunity for these scattered communities of researchers to coalesce into a single community.