Free It Began with Babbage by Subrata Dasgupta

rechenplan fertigung
” (“automatic machine code generation”). This coheres with the most common term used during the early 1950s:
automatic programming—
meaning, an environment that allowed the programmer to deploy symbolic notation to specify a program at a level of abstraction higher than that of the “real” machine itself. 17
    We see here the emergence of what, in present-centered language, would be called an
intermediate
or
virtual
machine more abstract than the actual physical computer. This virtual computer would be programmed in symbolic notation (representing the order code for the virtual machine), and the task of an automatic programming system would be to translate mechanically this virtual machine program into the order code for the real machine. The virtual machine was easier to program than the real machine but the two were closely coupled. Most such systems, during the early 1950s, entailed, or were elaborations of, assembly languages and assemblers, which translated the assembly language programs into the real machine’s “native” language in the manner pioneered by Wheeler in Cambridge for the EDSAC (see Chapter 9 , Section VI). The term automatic programming would prevail through the 1950s. In 1954, the Symposium on Automatic Programming for Digital Computers was held in Washington, DC, sponsored by the Office of Naval Research; and in 1960, an annual publication bearing the title
Annual Review of Automatic Programming
was launched. This publication, with that title, continued until 1994.
V
    A certain thinking trend was, however, taking shape. This trend was toward abstraction—to move programming away, albeit cautiously, from the physical machine in a direction tending toward what humans found more natural for specifying computations. For those who were concerned with mathematical or scientific computations, this meant abstracting from the physical computer toward mathematical expressions and formulas. This was the reverse of what was previously the case. Beginning with Babbage and Lovelace, the strategy formerly had been to
reduce
mathematical thought to the level of the machine, to reduce algorithms to machine order code.
    But, by around 1954, this trend was being reversed. There were those who desired to express their programs in mathematical or algebraic notation itself. 18 Automatic programming now came to mean the use of programs to
translate
efficiently algorithmic expressions and formulas stated in a mathematical language into economic machine code. 19
    In fact, by 1952, the problem had been recognized as twofold: (a) to design a mathematical language in which to express computations and (b) to develop a programming system that could translate programs cheaply in such languages into efficient machine code. This was what Corrado Böhm (1923–), an Italian and later a distinguished theoreticalcomputer scientist, set about doing as a graduate student at ETH Zurich in 1950 to 1952. In his doctoral dissertation, Böhm described both a language and a complete translator for that language. 20 This was what Halcombe Laning (1920-2012) and N. Zierler set about doing at MIT, where they created a “program for translation of mathematical equations for Whirlwind I.” 21 This was what, in England, Alick Glennie (1925–2003) of the Royal Armament Research Establishment desired to do when he designed a system he called AUTOCODE for the Ferranti/Manchester Mark I computer (see Chapter 8 , section XIII, for more on the Manchester Mark I; the Ferranti Mark I was the industrial version of the Manchester University Mark I). Glennie—“the unsung hero” in the story of programming languages and automatic programming, according to Knuth and Pardo 22 —delivered a lecture on AUTOCODE at Cambridge University in February 1953 based on notes he had prepared in December 1952, 23 in which he asserted that programming notation must make it easier