Module SEO01 Software Evolution

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Module SE-O-01 Software Evolution
Topic 3 Software Aging
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Contents

• Software Aging by D. L. Parnas
• Lehmans Laws of Software Evolution

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Software Aging

• Programs, like people, get old. We cant prevent
  aging, but we can understand its causes, take
  steps to limit its effects, temporarily reverse
  some of the damage it has caused, and prepare for
  the day when the software is no longer viable.
  ... (We must) lose our preoccupation with the
  first release and focus on the long term health
  of our products.
• D.L. Parnas

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Software Aging?

• It does not make sense to talk about software
  aging!
• Software is a mathematical product, mathematics
  does not decay with time.
• If a theorem was correct 200 years ago, it will
  be correct tomorrow.
• If a program is correct today, it will be correct
  100 years from now.
• If a program is wrong 100 years from now, it must
  have been wrong when it was written.
• All of the above statements are true, but not
  really relevant.

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Software Does Age

• Software aging is gaining in significance
  because
• of the growing economic importance of software,
• software is the capital of many high-tech firms.

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Software Does Age

• The authors and owners of new software products
  often look at aging software with disdain.
• If only the software had been designed using
  todays languages and techniques
• Like a young jogger scoffing at an 86 year old
  man (ex-champion swimmer) and saying that he
  should have exercised more in his youth!

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The Causes of Software Aging

• There are two types of software aging
• Lack of Movement Aging caused by the failure of
  the products owners to modify it to meet
  changing needs.
• Ignorant Surgery Aging caused as a result of
  changes that are made.
• This one-two punch can lead to rapid decline in
  the value of a software product.

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Lack of Movement

• Unless software is frequently updated, its users
  will become dissatisfied and change to a new
  product.
• Excellent software developed in the 60s would
  work perfectly well today, but nobody would use
  it.
• That software has aged even though nobody has
  touched it.
• Actually, it has aged because nobody bothered to
  touch it.

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Ignorant Surgery

• One must upgrade software to prevent aging.
• Changing software can cause aging too.
• Changes are made by people who do not understand
  the software.
• Hence, software structure degrades.

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Ignorant Surgery (Contd)

• After many such changes nobody understands the
  software
• the original designers no longer understand the
  modified software,
• those who made the modification still do not
  understand the software.
• Changes take longer and introduce new bugs.
• Inconsistent and inaccurate documentation makes
  changing the software harder to do.

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The Cost of Software Failure

• Inability to keep up,
• reduced performance,
• decreasing reliability.

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Inability To Keep Up

• As software ages, it grows bigger.
• Weight gain is a result of the fact that the
  easiest way to add a feature is to add new code.
• Changes become more difficult as the size of the
  software increases because
• There is more code to change,
• it is more difficult to find the routines that
  must be changed.
• Result Customers switch to a younger product
  to get the new features.

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Reduced Performance

• As the size of the program grows, it places more
  demands on the computer memory.
• Customers must upgrade their computers to get
  acceptable response.
• Performance decreases because of poor design that
  has resulted from long-term ad-hoc maintenance.
• A younger product will run faster and use less
  memory because it was designed to support the new
  features.

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Decreasing Reliability

• As the software is maintained, errors are
  introduced.
• Many studies have shown that each time an attempt
  is made to decrease the failure rate of a system,
  the failure rate got worse!
• That means that, on average, more than one error
  is introduced for every repaired error.

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Decreasing Reliability (Contd)

• Often the choice is to either
• abandon the project
• stop fixing bugs
• For a commercial product, Parnas was once told
  that the list of known unrepaired bugs exceeded
  2,000.

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Reducing the Cost of SW Aging

• We should be looking far beyond the first release
  to the time when the product is old.
• Inexperienced programmers get a rush after the
  first successful compile or demonstration.
• Experienced programmers realize that this is only
  the beginning ...

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Reducing the Cost of SW Aging (Contd)

• Responsible, professional, organizations realize
  that more work is invested between the time after
  the first successful run and the first release
  than is required to get the first successful run.
• Extensive testing and rigorous reviews are
  necessary.

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Preventive Medicine

• Design for success
• Keep records (documentation)
• Seek second opinions (reviews)

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Design for Success

• Design for change.
• This principle is known by various names
• information hiding
• abstraction
• separation of concerns
• data hiding
• object-orientation

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Design for Change

• To apply this principle one begins by trying to
  characterize the changes that are likely to occur
  over the lifetime of a product.
• Since actual changes cannot be predicted,
  predictions will be about classes of changes
• changes in the UI
• change to a new windowing system
• changes to data representation
• porting to a new operating system ...

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Design for Change (Contd)

• Since it is impossible to make everything equally
  easy to change, it is important to
• estimate the probabilities of each type of change
• organize the software so that the items that are
  most likely to change are confined to a small
  amount of code

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Why is Design for Change Ignored?

• Textbooks fail to discuss the process of
  estimating the probability of change for various
  classes of changes.
• Programmers are impatient because they are too
  eager to get the first version working.
• Designs that result from this principle are
  different from the natural designs of the
  programmers intuition.

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Why is Design for Change Ignored? (Contd)

• Few good examples of the application of the
  principle. Designers tend to mimic other designs
  they have seen.
• Programmers tend to confuse design principles
  with languages.
• Many practitioners lack training in software
  development.

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Keeping Records (Documentation)

• Even when software is well designed, it is often
  not documented.
• When documentation is present it is often
• poorly organized
• inconsistent
• incomplete
• written by people who do not understand the system

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Documentation

• Hence, documentation is ignored by maintainers.
• Worse, documentation is ignored by managers
  because it does not speed up the initial release.

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Second Opinions (Reviews)

• In engineering, as in medicine, the need for
  reviews by other professionals is never
  questioned.
• In designing a building, ship, aircraft, there is
  always a series of design documents that are
  carefully reviewed by others.

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Reviews

• This is not true in the software industry
• Many programmers have no professional training in
  software at all.
• Emphasis of CS degrees on mathematics and
  science professional discipline is not a topic
  for a liberal education.
• Difficult to find people who can serve as quality
  reviewers no money to hire outsiders.
• Time pressure misleads designers into thinking
  that they have no time for proper reviews.
• Many programmers resent the idea of being
  reviewed.

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Reviews

• Every design should be reviewed and approved by
  someone whose responsibilities are for the
  long-term future of the product.

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Why is Software Aging Inevitable?

• Our ability to design for change depends on our
  ability to predict the future.
• We can do so only approximately and imperfectly.
• Over a period of years
• changes that violate original assumptions will be
  made
• documentation will never be perfect
• reviewers are bound to miss flaws ...

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Why is Software Aging Inevitable? (Contd)

• Preventive measures are worthwhile but anyone who
  thinks that this will eliminate aging is living
  in a dream world.

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Software Geriatrics

• Retroactive Documentation
• A major step in slowing the age of older
  software, and often rejuvenating it, is to
  upgrade the quality of the documentation.
• Retroactive Modularization
• Change structure so that each module hides a
  design decision that is likely to change.

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Software Geriatrics (Contd)

• Amputation
• A section of code has been modified so often, and
  so thoughtlessly, that it is not worth saving.
• Major Surgery (Restructuring)
• Identify and eliminate redundant components and
  gratuitous dependencies.

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Planning Ahead

• Its time to stop acting as if getting it to
  run was the only thing that matters.
• Designs and changes have to be documented and
  carefully reviewed.
• If its not documented, its not done.
• In other areas of engineering, product
  obsolescence is recognized and included in design
  and marketing plans.
• The same should be done for software engineering.

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Contents

• Software Aging by D. L. Parnas
• Lehmans Laws of Software Evolution

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Lehmans Laws of Evolution

• Program evolution dynamics is the study of the
  processes of software system change
• After major empirical studies, Lehman and Belady
  proposed a number of "laws" that seem to be
  applicable to all evolving software systems

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Lehmans Laws of Evolution

• Lehman's laws of software evolution
• Based on the evolution of IBM 360 mainframe OS
  over a period of 30 years
• M. M. Lehman, L. Belady. Program Evolution
  Processes of Software Change. Academic Press,
  London, 1985, 538pp.
• M. M. Lehman. Laws of Software Evolution
  Revisited. Lecture Notes in Computer Science
  1149, pp. 108-124, Springer Verlag, 1997
• Laws Reflect the cooperative activity of many
  individuals and organisational behaviour
• Influenced by thermodynamics
• Reflect established observations and empirical
  evidence
• An emerging theory of software process and
  software evolution, i.e., work in progress

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Lehmans Laws of Evolution

• Law 1 Continuing change
• Law 2 Increasing complexity
• Law 3 Self regulation
• Law 4 Conservation of organisational stability
• Law 5 Conservation of familiarity
• Law 6 Continuing growth
• Law 7 Declining quality
• Law 8 Feedback system

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Lehmans Laws of Evolution

• Law 1 Continuing change
• "An E-type program that is used in a real-world
  environment must be continually adapted, else it
  becomes progressively less satisfactory"
• Reasons
• Evolution of the environment (operational
  domain)
• Hence, increasing mismatch between the system and
  its environment
• Remark
• E-type programs E for Evolutionary
• Real-world problem Stakeholders mainly human
• Requirements and environment continuously
  evolving
• Continuous need for change

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Lehmans Laws of Evolution

• Law 2 Increasing complexity
• "As a program is evolved its complexity increases
  unless work is done to maintain or reduce it."
• Reasons
• Small changes are applied in a step-wise process
• Each patch makes sense locally, not globally
• Effort needed to reconcile accumulated changes
  with the overall performance goals
• techniques like refactoring and performance
  optimisation are needed

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Lehmans Laws of Evolution

• Law 3 Self regulation
• "Program evolution is a self-regulating process.
  System attributes such as size, time between
  releases and the number of reported errors is
  approximately invariant for each system release."

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Lehmans Laws of Evolution

• Law 4 Conservation of Organisational Stability
  (invariant work rate)
• "The average effective global activity rate on an
  evolving system is invariant over the product
  life time."
• Reasons
• Managerial decisions (on effort) are constrained
  by external forces (e.g., resources, complexity)
• In practice, the effective effort invested
  converges to a constant

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Lehmans Laws of Evolution

• Law 5 Conservation of Familiarity
• "Over the lifetime of a system, the incremental
  change in each release is approximately constant."

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Lehmans Laws of Evolution

• Law 6 Continuing Growth
• "Functional content of a program must be
  continually increased to maintain user
  satisfaction over its lifetime."
• Implies the first law, except with focus on
  functional requirements
• often one cannot afford to omit existing
  functionality
• omitted attributes will become the bottlenecks
  and irritants in usage as the user has to replace
  automated operation with human intervention.
  Hence they also lead to demand for change

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Lehmans Laws of Evolution

• Law 7 Declining Quality
• "E-type programs will be perceived as of
  declining quality unless rigorously maintained
  and adapted to a changing operational
  environment."
• Implies the first law, except with focus on
  observed reliability
• Reasons
• Principle of Software Uncertainty Real world
  outcome of E-type software execution is
  inherently uncertain with precise area of
  uncertainty also not knowable.

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Lehmans Laws of Evolution

• Law 8 Feedback system
• "E-type programming processes constitute
  multi-loop, multi-level feedback systems and must
  be treated as such to be successfully modified or
  improved."
• Emphasis on feedback from team members in an
  organization

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Lehmans Laws of Evolution

• Applicability of Lehmans laws
• Lehmans laws seem to be generally applicable to
  large, tailored systems developed by large
  organisations.
• Confirmed in more recent work by Lehman on the
  FEAST project
• It is not (yet) clear whether they are applicable
  to
• Shrink-wrapped software products
• Systems that incorporate a significant number of
  COTS components
• Small organisations
• Medium sized systems
• Open source software