Can we build software faster and better and cheaper?

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.

Understanding the Value of Software Engineering Technologies

“…SEESAW is a variant of MaxWalkSat we first reported in [12]. While searching the ranges of a feature, this algorithm exploits the monotonic nature of Equation 5 and Equation 6.…”

“…Fortunately, we have found that the USC COCOMO and COQUALMO models [38] are "just right". In all our studies [8]- [12] we have found that prediction variance can be controlled by only constraining project options while letting the tuning variance remaining unchecked. Hence, we use these models for our research.…”

“…For this study, we use b = f = c = 1. In other work, we have explored the effects of using other b, f, c values [12]. In Equation 7,T ,Ē,D are the time, effort, and defect scores normalized zero to one.…”

“…The improvement resulting from that change would be obscured by the tuning variance. Previously we have reported some success with stochastic AI tools that search through the space of possible tunings within process models [8]- [12]. This approach returned conclusions about the project that were stable across the entire space of possibilities.…”

Case-based reasoning vs parametric models for software quality optimization

“…SEESAW was first introduced in [18] and has been applied to numerous domains [10,16,17,[20][21][22]. W was first introduced in [8] but that report includes no comparisons with other quality optimizers.…”