> custom font ROMs or typeballs Yup. Used those. I had a PC rigged with a toggle switch and a custom little wire-wrapped board to be able to switch character

> custom font ROMs or typeballs Yup. Used those. I had a PC rigged with a toggle switch and a custom little wire-wrapped board to be able to switch character ROMs. I even wrote printing utilities to be able to pause and swap out the IBM printer's type ball when printing documents that required a mixture of APL code segments and regular text. I wrote a custom hybrid text editor in APL for precisely this purpose, to be able to do application notes that included both character sets. > I think the "font problem" really was a significant issue for APL adoption during the period 01968–01988 Yes, agreed. The bit of APL history casual observers miss is that Iverson's motivation for transliterating APL symbols into J was exactly this problem. He tried to solve a business/financial/adoption problem. As a result, he bifurcated and confused the APL world. He was wrong to make this decision. And, what ended-up happening was that both languages became oddities rather than what APL could have become with the capabilities of next generation hardware. That and the cost of licenses. As a student I got free licenses but it was hard to justify what some of these packages cost. STSC's, I think, was the lowest cost most popular version used by most of the university types I used to engage with. IBM's version had penetration into business because of their position with mainframes. Once again, splitting the ecosystem did not do anyone any favors. J is an abomination (it defecates all over Iverson's own seminal paper on the power and value of notation as a tool for thought). APL had many issues that truly needed resolving. Simple things like the object oriented programming and heterogenous data types would have been very interesting to explore. The other thing may have been providing official means for avoiding O(n^2) issues where just a few innocent looking operators would result in converting vectors intro matrices or >2 dimensional arrays and then having to do all that processing when a simpler procedural option that does not expand to consume all available memory would have been great. In some ways this is the world of Python and numpy today. You can work at various levels of abstraction and be reasonably aware and in control of resources and computational complexity.