Computer Science is Not Bad Physics

Methodological meta-studies became popular in computing in the 1990s. Their aim was to survey large samples of papers in computing to find out facts about methodology in computing disciplines. Literally dozens of well done methodological reviews of computing were done, and the findings were unsurprising: Computing is a methodologically eclectic field. Those meta-studies were useful for computing’s disciplinary discussions: they replaced anecdotal evidence with empirically justified data.

Alas, many of them made assumptions that some of us might be unhappy about. Many of them used categorization schemes from other fields. Some measured quality by quantity: more lines about methodology, the better. Many used samples that were biased towards very specific publishing venues.

But the biggest problem, in my opinion, was that many of them had overt or covert normative intentions: They did not stop at describing what computing is, but went to to prescribe what it should be instead. (Hume’s guillotine, anyone?) Some compared research in computing with research in other fields, and argued that because some things were different between field X and computing, computing should be improved. And there’s the problem. Why should computing’s publishing profile look similar to that of optical engineering or physics? If you use the criteria of physics or anthropology to evaluate computing, what will you learn? You’ll learn that if computing were physics, it would be bad physics; and if computing were anthropology, it would be bad anthropology. But computing is a unique science with its own methods, approaches, and research agenda — and hence, one should be careful to compare research in computing with research in other independent disciplines.

What is more, it seems that many sciences are turning out to become more like computing than computing turning out to be more like them.



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