Software practices in industry are subjected to a ruthless Darwinian selection. Current best practices represent the least expensive and most effective way to safely develop reliable software.

Many large scientific software systems, even those in operational use, do not use these proven tools. Efforts to improve process are often bogged down by technical difficulties, management neglect, or programmer resistance.

How can we successfully apply techniques like automated testing, continuous integration, code review, and other modern process elements to a sometimes unruly culture of scientific programming?