No Silver Bullet

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No Silver Bullet

• Essence and Accident in Software Engineering

By Mike Hastings
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Introduction

• There is no single development, in either
  technology or management technique, which by
  itself promises even one order-of-magnitude
  improvement within a decade in productivity, in
  reliability, in simplicity. Frederick P. Brooks,
  Jr. (1995)
• Software Projects Werewolves
• Innocent but capable of becoming a monster
• No Silver Bullets in Site

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Essence (Essential Difficulties)

• Inherent
• Data sets, Relationships among data items,
  Algorithms, Invocations of functions
• Complexity
• Conformity
• Changeability
• Invisibility

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Complexity

• No two parts are alike
• Scaling up requires increase in elements
• Results
• Communication issues
• Unreliability
• Usage difficulties
• Side effects from expansion

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Conformity

• Must adapt to the minds of various people
• Must adapt with a variety of applications

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Changeability

• Constant pressures for change
• Software is infinitely malleable
• All software changes
• Users find new uses
• New hardware forces change

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Invisibility

• Unvisualizable
• No floor plans
• Cannot display geometrically
• Robs the mind of powerful tools
• Leading cause of communication issues

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Accidental Difficulties

• Not inherent
• Three steps that attacked major difficulties
• High-level Languages
• Time Sharing
• Unified Programming Environments

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High-Level Languages

• What do they accomplish?
• Frees up most accidental complexity
• User friendly language
• Disregards problems from the machine level

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Time-Sharing

• Shortens system response time
• Allows for thought retention

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Unified Programming Environments

• Integrated libraries
• Unified file formats
• Pipes and filters
• Helped develop whole toolbenches
• Universal tools

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Hopes for Silver
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ADA AND OTHER HIGH-LEVEL LANGUAGE ADVANCES

• Ada a high-level language of the 1980s
• Pros
• Improvements in language concepts
• Focused on step-by-step solutions
• Encourages modern design
• Cons
• Just another high-level language
• Low payoff after accidental complexity removal

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OBJECT-ORIENTED PROGRAMMING

• Two ideas Abstract Hierarchial
• Pros
• Avoids displaying unnecessary syntax
• Allows a higher-order-sort of design
• Cons
• Makes no change to essential complexity of the
  design

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ARTIFICIAL INTELLIGENCE

• Pros
• Using computers to solve problems only humans
  used to solve
• Cons
• Deciding what to say, not saying it

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EXPERT SYSTEMS
EXPERT SYSTEMS

• Pros
• Use of human experts to develop rules of thumb
• Inference Engine Rule Base to solve problems
• Cons
• Difficult to develop
• Knowledge acquisition

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AUTOMATIC PROGRAMMING

• Pros
• Solving a problem from problem specifications
• Already proven to work
• Cons
• The solution method is usually required, not the
  problem

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GRAPHICAL PROGRAMMING

• Pros
• Applying computer graphics to software design
• Flowchart construction
• Cons
• Flow charts are poor abstractions
• Todays screens are too small
• Software is difficult to visualize

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PROGRAM VERIFICATION

• Pros
• Error elimination in design phase
• Secure operating system kernels
• Cons
• Does not save labor
• Does not mean error proof

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ENVIRONMENTS AND TOOLS

• Pros
• Use of integrated databases to track details
• Cons
• Only marginal gains in efficiency

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WORKSTATIONS

• Pros
• Faster processing time
• Cons
• Still crippled by human "think time"

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Promising Attacks on the Conceptual Essence

• Attacks on accidental difficulties are limited by
  the productivity equation
• Time of Task ? (Frequency) x (Time)
• Conceptual components are time consuming
• Attacks must then address the essence of software
  problems

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BUY VERSUS BUILD

• Do not construct it at all
• Increase in products available for purchase
• Delivery is immediate
• Sharing cuts per-user cost
• Adapt operation processes

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REQUIREMENTS REFINEMENT AND RAPID PROTOTYPING

• Decide what to build
• Technical requirements
• Interfaces
• Obtain product requirements
• Rapid prototyping
• Simulates interfaces
• Performs main functions
• Minimizes hardware, and cost constraints

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INCREMENTAL DEVELOPMENT--GROW, NOT BUILD, SOFTWARE

• The brain is grown, not built
• Software should be similar
• Incremental development
• Make it run
• Top-down growing design
• Allows for easy backtracking
• Lends itself to early prototypes
• New functions grow organically
• Easier for teams to grow than build

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GREAT DESIGNERS

• Great designs come from great designers
• Software construction is a creative process
• Can empower the creative mind
• Great designers are rare
• How to grow great designers
• Identify them early
• Assign a career mentor
• Devise a development plan
• Allow them to interact with other growing
  designers

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SUMMARY

• Most accidental difficulties have been addressed
• Focus on improving essential difficulties
• Exploiting the mass market
• Using rapid prototyping
• Growing software organically
• Developing great conceptual designers

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THE END!!!