Sinopsis
This book is a comparative evaluation of three different approaches to transformational programming known as the Munich CIP project, Algorithmics, and RAPTS. Transformational programming is a methodology that formalizes the development of programs from problem specifications. The CIP approach relies on a strongly typed language with user-defined algebraic types and a semi-automatic transformation system requiring user guidance. Algorithmics is a pure pencil-and-paper approach to transformational programming, providing concise, uniform mathematical notation that includes work on nondeterminism. RAPTS is a fully mechanical system that transforms high-level specifications to C code. Given in a functional subset of SETL augmented with fixed-point operations, the specifications are transformed into efficient code which corresponds to different phases of the compiler. The author's detailed exploration provides common criteria by which such different transformational systems can be evaluated. This examination is useful for those seeking to understand the nuances of various transformational programming approaches.
Reseña del editor
Excerpt from Comparing Three Approaches to Transformational Programming
Programming is a complex task; large programs are difficult to produce, and once produced they are often unreliable and expensive to maintain or improve. The software crisis remains an important issue in software engineering. A large amount of research has been going on to overcome this crisis: On one hand, a considerable portion of the work has focused on formalizing and automating the software development process; on the other hand, prototyping has been promoted as a method of obtaining information about a problem before implementing it in a production language.
Traditionally, programs have been verified experimentally by choosing a number of input test cases, running the program, and evaluating the results. -the problem with this approach is that it can never formally prove the correctness of the program. There might always be cases not captured by the test data. Prototyping attempts to catch errors at an early a stage of the program development.
Formal verification, on the other hand, is an analytic process that defines in mathematical terms what it means for a program to be correct, given a mathematical definition of the program ming language used, and a formal specification of the problem being solved. However, the formal verification of large programs has turned out to be impractical.
By contrast, the transformational approach (see [pss3] for an excellent survey) is a synthetic or constructive one. A program is derived from a problem specification by successive application of correctness-preserving transformations that lead to a correct implementation of the problem. A key point is the reusability of transformation rules; once a rule is proven correct, it can be used again if applicable to the particular situation. Libraries of known transformations can be established; as the libraries grow, the number of new proofs required in the development of a. Program decreases.
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