@article {12162,
	title = {The Use of Empirical Studies in the Development of High End Computing Applications},
	year = {2009},
	month = {2009/12//},
	institution = {University of Maryland, College Park},
	abstract = {This report provides a description of the research and development activities towards learning much about the development and measurement of productivity in high performance computing environments. Many objectives were accomplished including the development of a methodology for measuring productivity in the parallel programming domain. This methodology was tested over 25 times at 8 universities across the United States and can be used to aid other researchers studying similar environments. The productivity measurement methodology incorporates both development time and performance into a single productivity number. An Experiment Manager tool for collecting data on the development of parallel programs, as well as a suite of tools to aid in the capture and analysis of such data was also developed. Lastly, several large scale development environments were studied in order to better understand the environment used to build large parallel programming applications. That work also included several surveys and interviews with many professional programmers in these environments.},
	keywords = {*COMPUTER PROGRAMMING, *EMPIRICAL STUDIES, *HPC(HIGH PERFORMANCE COMPUTING), *METHODOLOGY, *PARALLEL PROCESSING, *PARALLEL PROGRAMMING, *PRODUCTIVITY, *SOFTWARE ENGINEERING, *SOFTWARE METRICS, ADMINISTRATION AND MANAGEMENT, APMS(AUTOMATED PERFORMANCE MEASUREMENT SYSTEM), COMPUTER PROGRAMMING AND SOFTWARE, COMPUTER SYSTEMS MANAGEMENT AND STANDARDS, data acquisition, efficiency, ENVIRONMENTS, HIGH END COMPUTING, HPCBUGBASE, HUMAN FACTORS ENGINEERING \& MAN MACHINE SYSTEM, learning, measurement, MPI(MESSAGE PASSING INTERFACE), PARALLEL ORIENTATION, PE62303E, PROGRAMMERS, SE(SOFTWARE ENGINEERING), SUPERVISORS, TEST AND EVALUATION, TEST FACILITIES, EQUIPMENT AND METEORS, TIME, tools, United States, WUAFRLT810HECA},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA511351},
	author = {Basili, Victor R. and Zelowitz,Marvin V}
}
@article {18432,
	title = {Software Process Improvement in the NASA Software Engineering Laboratory.},
	year = {1994},
	month = {1994/12//},
	institution = {CARNEGIE-MELLON UNIV PITTSBURGH PA SOFTWARE ENGINEERING INSTITUTE},
	abstract = {The Software Engineering Laboratory (SEL) was established in 1976 for the purpose of studying and measuring software processes with the intent of identifying improvements that could be applied to the production of ground support software within the Flight Dynamics Division (FDD) at the National Aeronautics and Space Administration (NASA)/Goddard Space Flight Center (GSFC). The SEL has three member organizations: NASA/GSFC, the University of Maryland, and Computer Sciences Corporation (CSC). The concept of process improvement within the SEL focuses on the continual understanding of both process and product as well as goal-driven experimentation and analysis of process change within a production environment.},
	keywords = {*AWARDS, *SOFTWARE ENGINEERING, *SYSTEMS ANALYSIS, *WORK MEASUREMENT, ADMINISTRATION AND MANAGEMENT, COMPUTER PROGRAMMING AND SOFTWARE, COMPUTER PROGRAMS, COMPUTERS, data acquisition, ENVIRONMENTS, EXPERIMENTAL DATA, GROUND SUPPORT., measurement, Organizations, PE63756E, Production, SOFTWARE PROCESS IMPROVEMENT, SPI(SOFTWARE PROCESS IMPROVEMENT), SPN-19950120014},
	url = {http://stinet.dtic.mil/oai/oai?\&verb=getRecord\&metadataPrefix=html\&identifier=ADA289912},
	author = {McGarry,Frank and Pajerski,Rose and Page,Gerald and Waligora,Sharon and Basili, Victor R.}
}
@article {18415,
	title = {Program complexity using Hierarchical Abstract Computers},
	journal = {Computer Languages},
	volume = {13},
	year = {1988},
	month = {1988///},
	pages = {109 - 123},
	abstract = {A model of program complexity is introduced which combines structural control flow measures with data flow measures. This complexity measure is based upon the prime program decomposition of a program written for a Hierarchical Abstract Computer. It is shown that this measure is consistent with the ideas of information hiding and data abstraction. Because this measure is sensitive to the linear form of a program, it can be used to measure different concrete representations of the same algorithm, as in a structured and an unstructured version of the same program. Application of the measure as a model of system complexity is given for {\textquotedblleft}upstream{\textquotedblright} processes (e.g. specification and design phases) where there is no source program to measure by other techniques.},
	keywords = {CASE tools, complexity, ENVIRONMENTS, measurement, Prime programs},
	isbn = {0096-0551},
	doi = {10.1016/0096-0551(88)90019-7},
	url = {http://www.sciencedirect.com/science/article/pii/0096055188900197},
	author = {Bail,William G and Zelkowitz, Marvin V}
}
