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The Case for Inductive Programming
January 1997 (vol. 30 no. 1)
pp. 36-41

The science of creating software is based on deductive methods. But induction, deduction's ignored sibling, could have a profound effect on the future development of computer science theory and practice.

Computer scientists and software developers in the late 1960s started a formal science to guide software production. The underlying framework of this science has always been based on deduction (reasoning from the general to the specific) rather than induction (reasoning from the specific to the general).

Today inductive programming is found only in "machine learning," a subset of artificial intelligence. Computer scientists may use inductive techniques to explore a philosophy of cognition, develop a theory of adaptive behavior, or find a way around a particularly awkward problem, but they do not use it to create programs. Nearly all basic computing science textbooks fail to include inductive programming.

However, inductive reasoning can solve problems outside the realm of machine learning, too. Formal methods to underpin inductive techniques are emerging, but they have yet to be viewed, accepted, and developed as a fundamental alternative to deductive computer science.

Citation:
Derek Partridge, "The Case for Inductive Programming," Computer, vol. 30, no. 1, pp. 36-41, Jan. 1997, doi:10.1109/2.562924
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