On a “Buzzword”

Hierarchical Structure

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Team 1

CS575 – Software DesignBob Hazen, Mike Mangos, Tim

Santucci, Chris Dahn

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Historical Context

1974 No GUIsNo IDEsOnly thing available is code and imagination.

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Buzzwords

Parnas uses “hierarchical structures” as his exampleAlone, buzzwords do not convey information Remove definition from a technical

explanation

How do buzzwords occur? Ambiguity – Can mean different things to

different people

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Structures

T.H.E. system Program hierarchy, abstract machines Haberman hierarchy, work relationship

RC4000 Resource hierarchy

Multics Access hierarchy, protection hierarchy

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Structure Happens

IntentionalAnalytical heuristic After the fact

How are they useful? (T.H.E.) Structure is irrelevant to the

machine, only useful to the developers (RC4000) Structure is relevant to the

operation of the machine, not necessarily useful to the developers

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Object Oriented Programming

SmalltalkC++JavaC?

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Smalltalk

“Pure” OOP

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C++

EncapsulationPolymorphismInheritanceFriends

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Java

EncapsulationPolymorphismInheritance

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C

Supposedly not OOPGTK library button struct used as argument to

generic click() function

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Commercial Off The Shelf Software

Types of COTS Software End user applications System components Libraries

Beliefs Management Developer End User

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Beliefs: Management

Cheap Economies of scale Outsourcing the programming

Reliable

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Beliefs: Developer

More expensive Learning to work with it Verify versions of COTS Software

Not always flexible Buggy binary libraries Poor documentation

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Beliefs: End User

Expects it to work “off the shelf” Compounded SE problems

User may need to provide COTS Software Compatibility issues Web of dependencies

Redhat Linux RPMs

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Moral

Must be clear, concise and intelligent Buzzwords are inevitable

Okay, in the proper context Don’t take things for granted

“Hierarchical structures” was holding back software architectureQuestioning popular modes of thinking eliminates stale ideas

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“Artificial Intelligence”

Turing TestSearch AlgorithmsMachine Vision

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Turing Test

What is it? Communication using natural

language

Implementation is variableMimics human behavior

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Search Algorithms

Deep Blue vs. KasparovFocuses on single best answer/moveImplementation is specificMimics human decision making

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Machine Vision

Face recognitionFocused on pattern recognitionMimics human visual recognition