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Good Policy Makes Good Science

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Page 1: Good Policy Makes Good Science

May/June 2010 Copublished by the IEEE CS and the AIP 1521-9615/10/$26.00 © 2010 IEEE 5

F r o m T h e E d i t o r s

i begin with an apology. in a recent issue of CiSE, an article

included an example of the now infamous “lena” image. lena

is a standard test image originally cropped from a Playboy maga-

zine centerfold. this image should not have appeared in CiSE;

in the future, we’ll try to ensure that it doesn’t happen again.

in a 1999 essay on reasons for the male predominance in computer science (see www.cs.umd.edu/users/oleary/faculty/whole.html), dianne o’leary wrote:

“If a professor makes a sexist joke, a female student might well find it so disturbing that she is unable to listen to the rest of the lecture. Suggestive pictures used in lectures on image processing are similarly distracting to the women lis-teners and convey the message that the lecturer caters to the males only. For example, it is amazing that the ‘lena’ pin-up image is still used as an example in courses and published as a test image in journals today.”

i share o’leary’s opinion and apologize to our readers for the image’s appearance in CiSE. some people claim that the lena image contains a nice mixture of detail, flat regions, shad-ing, and texture that do a good job of testing various image processing algorithms. this might well be true, but surely there are better images that don’t cause the bad feelings that lena’s picture does. we need excellence in computational sci-ence, and we need to attract and keep creative people in the field. it doesn’t serve our profession to alienate half the popu-lation. i also argue that the overuse of “standard” test data isn’t the best way to check new methods and algorithms.

how do we know that a program computes what we in-tend it to compute? put another way, how do we know that our program will give a correct answer for every input we’re planning to use? the answer to the most general form of this question is that we don’t know because the halting problem can be formulated about a question about correct-ness. of course, if we really believed that we can’t know a program is correct, we’d never get in a car that uses comput-ers. we would not get into an airplane, and we would not trust our lives to certain medical devices.

in the case of scientific computing, we often rely on two things—one obvious, and the other more subtle. the obvious one is to debug carefully and run lots of com-putations on test cases for which the answer is already known. the more subtle way to assure ourselves of cor-rectness is to seek physical or mathematical insight into the problem at hand. insight is really just the sum of our expe-riences. in this case, it means we have some notion of what a correct answer should look like. if we see something un-expected, we start rechecking and, if we’re very lucky, end up reporting the discovery of a new phenomenon rather than a deep and previously undiscovered bug.

the obvious approach to establishing correctness often leads to the almost universal use of standard sets of

test data. but using the same test data again and again will never lead to finding bugs that don’t occur in processing the test data—and it certainly won’t lead to the discovery of new phenomena and methods.

so, perhaps it’s time to retire lena’s picture or at very least put to rest the tired justifications for her repeated ap-pearance at the expense of good policy and good science.

i’m grateful to francis sullivan for interesting conversa-tions on software testing.

Good Policy Makes Good scienceBy Isabel Beichl, Editor in Chief

Write for CiSE

CiSE publishes a range of article types, including opinion pieces, tutorials on useful and interest-

ing topics, and reports on research in the practice and application of computational science. A peer-reviewed publication that appears six times per year, CiSE is read by thousands of scientists and engineers active in a vari-ety of disciplines. For more information, guidelines, and our editorial calendar, visit us at www.computer.org/cise.

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