Information Technology Reference
In-Depth Information
the need for expensive programming talent.
2
The computer would
program itself.
Despite their associations with deskilling and routinization, automatic
programming systems could also work to the benefi t of occupational
programmers and academic computer scientists. High-level program-
ming promised to reduce the tedium associated with machine coding,
and allowed programmers to focus on more system-oriented—and high-
status—tasks such as analysis and design. Language design and develop-
ment served as a focus for productive theoretical research, and helped
establish computer science as a legitimate academic discipline. And auto-
matic programming systems never did succeed in eliminating the need
for skilled programmers. In many ways, they contributed to the elevation
of the profession, rather than the reverse, as was originally intended by
some and feared by others.
In order to understand why automatic programming languages were
such an appealing solution to the software crisis as well as why they
apparently had so little effect on the outcome or severity of the crisis, it
is essential to consider these languages as parts of larger social and
technological systems. This chapter will describe the emergence of pro-
gramming languages as a means of managing the complexity of the
programming process. It will trace the development of several of the most
prominent automatic programming languages, particularly FORTRAN
and COBOL, and situate these technologies in their appropriate histori-
cal context. Finally, it will explore the signifi cance of these technologies
as potential solutions to the ongoing software crisis of the late 1950s
and early 1960s.
Assemblers, Compilers, and the Origins of the Subroutine
At the heart of every automatic programming system was the notion that
a computer could be used, at least in certain limited situations, to gener-
ate the machine code required to run itself or other computers. This was
an idea with great practical appeal: although programming was increas-
ingly seen as a legitimate and challenging intellectual activity, the actual
coding of a program still involved tedious and painstaking clerical work.
For example, the single instruction to “add the short number in memory
location 25,” when written out in the machine code understood by most
computers, was stored as a binary number such as 111000000000110010.
This binary notation was obviously diffi cult for humans to remember
and manipulate. As early as 1948, researchers at Cambridge University
