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Can We Build Software Faster and Better and Cheaper?

[document] Submitted on 17 September, 2019 - 09:17
Keywords Can We Build Software Faster and Better and Cheaper? software engineering predictor models COCOMO Faster Better Cheaper simulated annealing software processes
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Some within NASA, like 30 year veteran Frank Hoban, supported
these policies [18] who viewed these new policies as a necessary
break from traditional policies that were very risk averse.
The additional cost reduction, accompanied by the additional risk,
was to allow for a path to cheap and commercial space flight. Even
given the reduced funding, the Mars Pathfinder mission, along with
other first generation FBC missions, were successes. This fueled
enthusiasm to apply FBC across all of NASA to further reduce
spending per mission as well cutting the work force by one third.

FBC was extended to be applied on manned space missions as well,
where funding was also reduced. Coming into a space shuttle program
that was starting to age and in need of updates, the new policies
imposed cuts in funding from 48% of the NASA budget to
38% [15], further straining that program. Further more, a single
prime contractor (Lockheed Martin) was used for missions in another
bid to reduce cost and managerial complexity [36, 38].

This produced opposition within NASA, where traditionally issues
pertaining to the shuttle were designated LOVC (Loss of Vehicle
and Crew) and given priority over all other issues, including
cost. However the cost cuts and layoffs that ensued damaged
morale leading to a string of early retirements of veteran scientists,
skilled engineers and managers [15].

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UNKNOWN
Document type
technical white paper
Pages
9
Replaced/Superseded by document(s)
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Abstract

“Faster, Better, Cheaper” (FBC) was a development philosophy
adopted by the NASA administration in the mid to late 1990s. that
lead to some some dramatic successes such as Mars Pathfinder as
well as a number highly publicized mission failures, such as the
Mars Climate Orbiter & Polar Lander. The general consensus on FBC was “Faster, Better, Cheaper? Pick any two”. According to that view, is impossibly to optimize on all three criteria without compromising the third. This paper checks that view using an AI search tool called STAR. We show that FBC is indeed feasible and produces similar or better results when compared to other methods However, for FBC to work, there must be a balanced concern and concentration on the quality aspects of a project. If not, “FBC” becomes “CF” (cheaper and faster) with the inevitable lose in project quality.

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