Testing and distribution of the RPS2 proposal submission system

Robert E. Douglas Jr.

doi:10.1117/12.316476

3 July 1998 Testing and distribution of the RPS2 proposal submission system

Robert E. Douglas Jr.

Proceedings Volume 3349, Observatory Operations to Optimize Scientific Return; (1998) https://doi.org/10.1117/12.316476
Event: Astronomical Telescopes and Instrumentation, 1998, Kona, HI, United States

Abstract

In 1995, the Space Telescope Science Institute (STScI) introduced RPS2 (Remote Proposal Submission 2). RPS2 is used by Hubble Space TElescope (HST) proposers to prepare their detailed observation descriptions. It is a client/server system implemented using Tcl/Tk. The client can transparently access servers on the user's machine, at STScI, or on any other machine on the Internet. The servers combine syntax checking, feasibility analysis and orbit packing, and constraint and schedulability analysis of user- specified proposals as they will be performed aboard HST. Prior to the release of RPS2, observers used a system which provided only syntax checking. RPS2 now provides the observers with some of the more complicated pieces of software that had been used by STScI staff to prepare observations since 1990. The RPS2 system consists of four independent subsystem, controlled by the client/server mechanism. A problem with a system of this size and complexity is that the software components, which continue to grow and change with HST itself, must continually be tested and distributed to those who need it. In the past, it had been acceptable to release the RPS2 software only once per observing cycle, but it became apparent before the 1997 HST Servicing Mission that multiple releases of RPS2 were going to be required to support the new instruments. This paper discusses how RPS2 and its component systems are maintained, updated, tested, and distributed.

Citation Download Citation

Robert E. Douglas Jr. "Testing and distribution of the RPS2 proposal submission system", Proc. SPIE 3349, Observatory Operations to Optimize Scientific Return, (3 July 1998); https://doi.org/10.1117/12.316476

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