Brittleness and Bureaucracy: Software as a Material for Science

tags

Software Development

Brittleness from cowboy coding vs drag from bureaucracy. Could see as simply putting your time suck up front vs at the back end, but affectively very different situations

Notes

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piecemeal growth exerts pressures on research through a tendency towards software brittleness.

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While countering brittleness, however, these steps themselves transformed the working environment, and placed new demands on research time that altered the nature of research, which some saw as a bureaucratic burden.

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The priority during the early life of Fluidity had always been to deliver the short-term aims of specific research projects, and there had been little time or money available to make the system maximally extensible.

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the fundamental problem with brittle code is not so much that it breaks more often—all code can be expected to break when being developed – it is that when it does break it is hard to figure out exactly why.

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Brittleness compromises habitability.

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The modelling environment is less conducive to just “trying things out”

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From a deductivist viewpoint interested in the validity of scientific discourse, brittle and robust codes make little difference.

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it would be a mistake to think about manipulability solely as a property of the software it- self. Everything depends on working practices.

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broad division within the research group, between on the one hand, those who self-identify as programmers and who are driven by epistemic interest in the code itself, and on the other hand, those who regard programming as a means to an end

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If brittleness is one “material” property of software environments, the tar pit is another, the feeling of density and sluggishness imposed by the additional organizational routines

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What the big organizations are after is something quite different: a “programming systems product.” This is not merely a big code. It is a code that “can be run, tested, extended or repaired by anybody… usable in many operating environments, for many sets of data…

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Brooks’ estimate is that to create a programming systems product requires nine times as much work as a program,

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axes of desire, emotion and excitement that drive research (Knorr-Cetina 2001, p.182). The picture this provides, however, needs to be filled out by exploring the other kinds of concern that cut across the epistemic, concerns with maintaining equipment under conditions of stress, of holding things together in arrangements that threaten to break down. These technical motivations are not isolated from epistemic motivations; they gain their force from the latter.

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