Artificial Intelligence and Software Engineering: by Derek Partridge

By Derek Partridge

During this literate and easy-to-read dialogue, Derek Partridge is helping us comprehend what AI can and can't do. themes mentioned contain strengths and weaknesses of software program improvement and engineering, the guarantees and difficulties of computer studying, specialist structures and luck tales, sensible software program via synthetic intelligence, synthetic intelligence and traditional software program engineering difficulties, software program engineering technique, new paradigms for approach engineering, what the longer term holds, and extra.

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Extra info for Artificial Intelligence and Software Engineering: Understanding the Promise of the Future

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But, working in precisely the opposite direction, the moves to more ambitious software projects (such as real-time and safety-critical applications as well as simply larger and more complex systems) has undermined, perhaps negated, the impact of the general improvements. So despite enormous advances within both the science and the technology of software design, it is not clear that the nature of the crisis has changed much, or lessened in severity. If there were, say, a similar long-term crisis in regular engineering then we would think twice before driving over a new bridge, resist the impulse to slam doors in buildings, and generally proceed with caution in order that these edifices and erections should not crack, split, break off at the edges, or even collapse into a more stable state of lower potential energy.

Subsequent verification of the claim that the algorithm designed correctly implements the specification. There are, of course, many detailed frameworks that will accommodate these two key ideas, but I shall lump them all together as the Specify-And-Verify or SAV approach to software system construction. Advocates of the SAV methodology have to face a number of problems even if they are concerned only with the implementation of conventional software systems. First, problem specifications can seldom be complete.

The myth of complete specification The first column in this table is very like the second column in the previous tabulation of problem-class differences (in Chapter 2). I have changed the column heading, but there's nothing significant in that. " Why did I do this? I did it because "fairly complete" is a more accurate characterization of the sort of specification available to practical software system designers. The notion of a "complete specification" is a convenient fiction that we could live with in Chapter 2, but now that your appreciation of the software engineer's task has matured I can tell it like it really is (and, of course, model computer science problems had not been separated off in Chapter 2 either).

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