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Designing Software for Ease of Extension and Contraction

Designing Software for Ease of Extension and Contraction. David Parnas Presented by Kayra Hopkins. IEEE Transactions on Software Engineering, Vol. , No. 1, March 1979 pp. 128-138. Presentation Outline. Problem Motivation Observations Contribution Example Impact Questions.

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Designing Software for Ease of Extension and Contraction

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  1. Designing Software for Ease of Extension and Contraction David Parnas Presented by Kayra Hopkins IEEE Transactions on Software Engineering, Vol. , No. 1, March 1979 pp. 128-138.

  2. Presentation Outline • Problem • Motivation • Observations • Contribution • Example • Impact • Questions

  3. Problem and Motivation • Problem • How can we design software so that is is easily extended and contracted? • Motivation • Complaints that most software systems as commonly/intuitively designed are not flexible. • Changes require a lot of code rewriting

  4. Overview of Contribution • Observations • Recognizing how the lack of Subsets and extensions manifests itself • The Technique: Steps towards a better structure

  5. Observations • A software solution isn’t a single program • Software as a family of programs • Change is inevitable • So why not anticipate it with preparation?

  6. How the lack of subsets and extensions manifests itself • Excessive Information Distribution • A Chain of Data Transforming Components • Components That Perform More Than One Task • Loops in “Uses” Relation

  7. Steps towards a better structure • Identify Subsets first • Solves problem of components with more than one function • Makes system more flexible to change • Information Hiding: Define Interfaces and Modules • Solves problem of excessive information distribution • Virtual Machine Concept • Addresses chain of data problem • Design the “Uses” Structure • Eliminates loops in the “uses” relation

  8. Steps towards a better structure(2) • Design the “Uses” Structure • Program A “uses” program B if function of A depends on correct implementation of B. • Structure has hierarchy. • Consequences • A is simpler because it uses B. • B doesn’t use A, so it doesn’t increase its complexity. • There exists a useful subset containing B and not A. • There isn’t a practical subset containing A but not B.

  9. Example: Address Processing Subsystem • Assumptions: • Specific address information is to be processed • Input formats are subject to change. Likewise with output formats. • For each system the format for input and output may be done in one of three ways. • Representations of address may be different for each system. • Only a subset of the addresses are needed in main memory at any given time.

  10. An Address Processing Subsystem • Design Decisions • Input and Output will be table driven • Representations of addresses in core will be the “secret” of an address storage module(ASM) • When the number of addresses to be stored exceeds the capacity of ASM, programs will use an address file module (AFM) • Implementation of AFM will use ASM as a submodule along with a block file module (BFM)

  11. An Address Processing Subsystem • Component Programs • Address Input Module • Address Output Module • Address Storage Module • Block File Module • Address File Module

  12. An Address Processing Subsystem • Uses Relation

  13. Impact • Modern Programming Languages • Class Diagrams • More Flexibility!

  14. Open Questions • What is a universal message that we can take away from this problem? • Could planning for change not be cost-effective?/Is there ever a situation that you would not want to plan for change? • Should this technique be modified for today’s problems and applications? If so, how?

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