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Information models of software productivity - Limits on productivity growthResearch into generalized information-metric models of software process productivity establishes quantifiable behavior and theoretical bounds. The models establish a fundamental mathematical relationship between software productivity and the human capacity for information traffic, the software product yield (system size), information efficiency, and tool and process efficiencies. An upper bound is derived that quantifies average software productivity and the maximum rate at which it may grow. This bound reveals that ultimately, when tools, methodologies, and automated assistants have reached their maximum effective state, further improvement in productivity can only be achieved through increasing software reuse. The reuse advantage is shown not to increase faster than logarithmically in the number of reusable features available. The reuse bound is further shown to be somewhat dependent on the reuse policy: a general 'reuse everything' policy can lead to a somewhat slower productivity growth than a specialized reuse policy.
Document ID
19930060921
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
Authors
Tausworthe, Robert C.
(JPL Pasadena, CA, United States)
Date Acquired
August 16, 2013
Publication Date
January 1, 1992
Publication Information
Publication: Journal of Systems and Software
ISSN: 0164-1212
Subject Category
Computer Programming And Software
Accession Number
93A44918
Distribution Limits
Public
Copyright
Other

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