[QR] Examples of successful open-source, bazaar development predating the Internet explosion and unrelated to the Unix and Internet traditions have existed. The development of the info-Zip compression utility during 1990-x1992, primarily for DOS machines, was one such example. Another was the RBBS bulletin board system (again for DOS), which began in 1983 and developed a sufficiently strong community that there have been fairly regular releases up to the present (mid-1999) despite the huge technical advantages of Internet mail and file-sharing over local BBSs. While the info-Zip community relied to some extent on Internet mail, the RBBS developer culture was actually able to base a substantial on-line community on RBBS that was completely independent of the TCP/IP infrastructure.
[CV] That transparency and peer review are valuable for taming the complexity of OS development turns out, after all, not to be a new concept. In 1965, very early in the history of time-sharing operating systems, Corbat? and Vyssotsky, co-designers of the Multics operating system, wrote
It is expected that the Multics system will be published when it is operating substantially... Such publication is desirable for two reasons: First, the system should withstand public scrutiny and criticism volunteered by interested readers; second, in an age of increasing complexity, it is an obligation to present and future system designers to make the inner operating system as lucid as possible so as to reveal the basic system issues.
[JH] John Hasler has suggested an interesting explanation for the fact that duplication of effort doesn't seem to be a net drag on open-source development. He proposes what I'll dub ``Hasler's Law'': the costs of duplicated work tend to scale sub-qadratically with team size-that is, more slowly than the planning and management overhead that would be needed to eliminate them.
This claim actually does not contradict Brooks's Law. It may be the case that total complexity overhead and vulnerability to bugs scales with the square of team size, but that the costs from duplicated work are nevertheless a special case that scales more slowly. It's not hard to develop plausible reasons for this, starting with the undoubted fact that it is much easier to agree on functional boundaries between different developers' code that will prevent duplication of effort than it is to prevent the kinds of unplanned bad interactions across the whole system that underly most bugs.
The combination of Linus's Law and Hasler's Law suggests that there are actually three critical size regimes in software projects. On small projects (I would say one to at most three developers) no management structure more elaborate than picking a lead programmer is needed. And there is some intermediate range above that in which the cost of traditional management is relatively low, so its benefits from avoiding duplication of effort, bug-tracking, and pushing to see that details are not overlooked actually net out positive.
Above that, however, the combination of Linus's Law and Hasler's Law suggests there is a large-project range in which the costs and problems of traditional management rise much faster than the expected cost from duplication of effort. Not the least of these costs is a structural inability to harness the many-eyeballs effect, which (as we've seen) seems to do a much better job than traditional management at making sure bugs and details are not overlooked. Thus, in the large-project case, the combination of these laws effectively drives the net payoff of traditional management to zero.
[HBS] The split between Linux's experimental and stable versions has another function related to, but distinct from, hedging risk. The split attacks another problem: the deadliness of deadlines. When programmers are held both to an immutable feature list and a fixed drop-dead date, quality goes out the window and there is likely a colossal mess in the making. I am indebted to Marco Iansiti and Alan MacCormack of the Harvard Business School for showing me me evidence that relaxing either one of these constraints can make scheduling workable.
One way to do this is to fix the deadline but leave the feature list flexible, allowing features to drop off if not completed by deadline. This is essentially the strategy of the "stable" kernel branch; Alan Cox (the stable-kernel maintainer) puts out releases at fairly regular intervals, but makes no guarantees about when particular bugs will be fixed or what features will beback-ported from the experimental branch.
