a person than is the corresponding machine language. This enhanced readability tends to decrease the number of programming errors found in any given segment of code.

Since assembly language is so close in form to machine language it is relatively easy to translate it into machine language. In particular, the translation operation can be accomplished in a single scanning pass through the assembly language representation. This makes for very efficient processing on computers that do not have large-scale forms of intermediate memory, as was the case on the earliest computers. Assembly language, however, is still very tightly associated with the sensori-motor environment of the computer. To address problems from the human domain of experience, it is extremely useful to have programming languages that are significantly closer to natural languages. This brings us to the high-level programming languages.

As computers grew more powerful, they offered sufficient capabilities to support the use of programming languages that were much closer in form and semantic content to the problems they were used to solve than were either machine languages or assembly languages. These languages are rather generically referred to as high-level languages. While they were close in form to the problems, they were still significantly less capable than the natural languages of human users of computers. We noted above that the earliest mainframe computers tended to be grouped into business-oriented and scientific-oriented systems. Consequently, the earliest high-level languages followed this same decomposition.

FORTRAN, which is an acronym that stands for FORmula TRANslation, has become a well-recognized name in its own right. It refers to a programming language that is very similar to mathematical formulas. FORTRAN has instructions that allow for procedural control of parametric information interspersed with the evaluation of various formulas that incorporate these same parameters. It has found widespread use within the scientific community as a means of dealing with problems that can be well expressed algorithmically. So, what does this really mean? Simply that many scientific oriented problems can be represented through algebraic formulas: one variable connected through an equal sign to a collection of variables related with arithmetic operations. With this type of representation, one seeks to address problems in which the variables in such a formula can be given values and then evaluated to an answer. In many instances, it is necessary to vary the values and parameters in a systematic way and to reevaluate the answer; a process sometimes called iteration.

A related, but also significantly different way to express certain problems is through recursion. A recursive formulation is typically a formula for a dependent variable that is expressed in terms of itself. Thus, to evaluate the formula, it is necessary to begin with some set of initial conditions, evaluate the dependent variable, and then plug that value back into the formula and evaluate the dependent variable again. This process is repeated until some related characteristic of the relationship indicates that the recursive process is to terminate. Historically FORTRAN had a serious deficiency in not being able to provide recursion in its operations. Although corrected in more recent versions, FORTRAN is nevertheless slowly being supplanted by other languages that have been found superior in dealing with more complex problems that are not exclusively within the scientific realm. As we have noted relative to a number of characteristics, including that of trust, recursion is an important concept relative to real-life problems.

Another early high-level language is COBOL. This acronym stands for COmmon Business Oriented Language, and it was (and still is) used as a mechanism to deal with business problems. We use the term business problems to rather specifically refer to problems couched in the context of finance; for example, working with equations dealing in currency and developing reports

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