Transcript Software Engineering - Computer and Information Science

Readings in Computer Science: Software Engineering
No Silver Bullet
Essence and Accidents of Software Engineering
Frederick P. Brooks, Jr.
Prepared by Jinzhong Niu
April 5, 2016
Frederick P. Brooks, Jr.
 Kenan Professor of CS at
Univ. of North Carolina - Chapel Hill
 Achievements
 IBM OS/360
 “The mythical Man-Month”
 Honors and Awards
 A.M. Turing Award, ACM (1999)
 National Medal of Technology (1985)
Readings in Computer Science: Software Engineering
NSB
2
About this paper
 Proc. IFIP Congress 1986, Information
Processing 86
 IEEE Computer, Vol. 20, No. 4, Apr. 1987
 The Mythical Man-Month, 2nd Edition, 1995
 Software Engineering, edited by Merlin
Dorfman and Richard Thayer, Wiley-IEEE Press

1st Edition, 1996

2nd Edition, 2002
Readings in Computer Science: Software Engineering
NSB
3
What are werewolves
and silver bullets?
Werewolf
 one of the oldest monster legends
 popular movie topic
Silver bullet
 the only thing that can kill werewolves
Even a man who is pure at heart,
And says his prayers at night,
Can become a wolf when the wolfbane blooms,
And the moon is full and bright.
-- From “The Wolf Man”
Readings in Computer Science: Software Engineering
NSB
4
“Essence” and “Accident”
 Essence

noun,
the permanent as contrasted with the
accidental element of being
 the mental crafting of the conceptual constructs
 Accident

noun,
a nonessential property or quality of an
entity or circumstance; appurtenant
(rather than misfortune or occurring by chance)
 the implementation process of conceptual constructs
Readings in Computer Science: Software Engineering
NSB
5
Overview
Software development is werewolf, but there is no
silver bullet because of its essential difficulties.

I.
What is the nature of software development?
(Why does it have to be hard?)
II.
Did past breakthroughs solve the problem?
III. Is there any potential solution nowadays?
IV. Will the problem be attacked in the future?
Readings in Computer Science: Software Engineering
NSB
6
Problem solving strategy
知己知彼，百战不殆。
—— 《孙子兵法》
Know your enemy and know yourself; in a hundred
battles, you will never be defeated.
--- SUN TZU ON THE ART OF WAR
Readings in Computer Science: Software Engineering
NSB
7
Why does software
engineering have to be hard?
Outside
 Computer hardware progress is an exception.
Inside
 There are essential difficulties which are hard
to be attacked.
Readings in Computer Science: Software Engineering
NSB
8
Essential difficulties
Complexity
Conformity
Changeability
Invisibility
Readings in Computer Science: Software Engineering
NSB
9
Essential difficulties:
Complexity
 A system is usually defined as a collection of
components, which interact with one another.
 Software is much more complex than any other
human construct.
 The number of elements
 The interaction between elements
Readings in Computer Science: Software Engineering
NSB
10
Essential difficulties:
Complexity --- Cont.
 A variety of problems are caused.
 Technical
 Decrease of reliability, usability, extensibility, safety
 Managerial
 Difficulty of communication between team members
 Difficulty of keeping a clear integrated overview and all the
loose ends
 Difficulty of personnel turnover due to tremendous learning
and understanding burden
Readings in Computer Science: Software Engineering
NSB
11
Why high complexity?
 Software varies.
 A colorful world needs colorful software systems, because
“software has become the dominant technology in many if not
most technical systems. It often provides the cohesiveness
and data control that enable a complex system to solve
problems.” [SwSE, Richard Thayer]
 A single piece of software involves high complexity.
 High conformity
Readings in Computer Science: Software Engineering
NSB
12
Essential difficulties:
Conformity
 Unlike physics where a terrible but invariable
complexity exists, software has to conform many
human institutions and system interfaces, the
number of which is still swelling all the time.
 Redesign of the software alone cannot simplify
out the complexity.
Readings in Computer Science: Software Engineering
NSB
13
Essential difficulties:
Changeability
Software is constantly subject to
pressures for change.
Successful software DOES change
frequently.
Readings in Computer Science: Software Engineering
NSB
14
Essential difficulties:
Changeability --- Cont.
 Why?
 Necessity:
Software embodies function, which most feels the
pressures of change in a system.
 Successful software is hoped to function over time.
 It is hoped to function in new domains.
 Feasibility:
Software, pure thought-stuff, is infinitely
malleable.
Readings in Computer Science: Software Engineering
NSB
15
Essential difficulties:
Invisibility
Software is invisible in the sense that it is
not inherently embedded in space.
Software structure is difficult to visualize
in a hierarchical fashion.
Readings in Computer Science: Software Engineering
NSB
16
Did past breakthroughs solve
the problem?
No. What they attacked are accidental
difficulties not essence.
Give me some examples!
 High-level languages
 Time-sharing
 Unified programming environments
Readings in Computer Science: Software Engineering
NSB
17
High-level languages
 The development of high-level languages is credited with
 at least a factor of five in productivity,
 concomitant gains in reliability, simplicity, and comprehensibility.
 It, however, eliminates only the complexity related to lower level
constructs that are not inherent in software.
 The level of our thinking about data structures, data types, and
operations is steadily rising, but at an ever decreasing rate, and
approaches closer and closer to the sophistication of users.
Readings in Computer Science: Software Engineering
NSB
18
Level of Abstraction
High-level languages --- Cont.
The sophistication level of human
Time
bits
registers
conditions
branches
channels
disks
...
int, float, double, …
variable, array, record, …
for, while, switch, …
…
object
class
messages
...
Readings in Computer Science: Software Engineering
NSB
19
Time-sharing
 Time-sharing eliminates the slow turnaround of
batch programming, and keeps fresh in mind the
grasp of a complex system.
 The benefit of time-sharing is to be boundary due
to the human threshold of noticeability.
Readings in Computer Science: Software Engineering
NSB
20
Unified programming
environments
 Unified programming environments enable related
individual tools to work together in an automatic
manner. They thus free programmers from the
burden of various manual operations.
 By its very nature, the fruit is and will be marginal.
Readings in Computer Science: Software Engineering
NSB
21
Is there any potential
solution nowadays?
 Ada and other high-level language advances ?
 Object-oriented programming ?
 Artificial Intelligence ?
 Expert Systems ?
 “Automatic” programming ?
 Graphical programming ?
 Program verification ?
 Environments and tools ?
 Workstations ?
Readings in Computer Science: Software Engineering
NSB
22
Ada
 Ada, one of the most touted recent development,
not only reflects evolutionary improvements in
language concepts, but indeed embodies features to
encourage modern design and modularization.
 Nevertheless, it is just another high-level language
and will not prove to be the silver bullet.
Readings in Computer Science: Software Engineering
NSB
23
Object-oriented
programming
 Two orthogonal concepts representing real advances:
 abstract data types
 hierarchical types
 OO Concepts:





encapsulation
abstraction
inheritance
polymorphism
dynamic binding
Readings in Computer Science: Software Engineering
NSB
24
Object-oriented
programming --- Cont.
 OO represents real advances in the art of
building software.
 Nevertheless, they remove only accidental
difficulties from the expression of the
design, rather than the design itself.
Readings in Computer Science: Software Engineering
NSB
25
Artificial Intelligence
Terminological chaos – Two definitions:
 AI-1: The use of computers to solve problems
that previously could only be solved by applying
human intelligence.
 AI-2: The use of a specific set of programming
techniques known as heuristic or rule-based
programming.
(expert system)
Readings in Computer Science: Software Engineering
NSB
26
Artificial Intelligence --Cont.
 AI advancements facilitate HCI (Human
Computer Interface).
 However, the hard thing about building
software is deciding what to say, not how
to express.
Readings in Computer Science: Software Engineering
NSB
27
Expert Systems
 Definition:
 a program containing a generalized inference engine and a rule base,
takes input data and assumptions, explores the inferences derivable
from the rule base, yields conclusions and advice, and explains its
results by retracting its reasoning for the user
 Advantages:
 Inference-engine technology is application-independent.
 The application-peculiar materials are encoded in the rule base in a
uniform fashion, which regularizes the complexity of the application
itself.
Readings in Computer Science: Software Engineering
NSB
28
Expert Systems --- Cont.
User
Interface
Input
data
Knowledge Base
(Rules, Facts)
User
Inference Engine
advices
Readings in Computer Science: Software Engineering
NSB
29
Expert Systems --- Cont.
 Possible benefits:
 Expert systems in software engineering field
 Building software in the way expert systems work
 Difficulties
 How to generate automatically the diagnostic rules from
program-structure specification
 How to extract expertise and distill it into rule bases
Readings in Computer Science: Software Engineering
NSB
30
“Automatic” programming
 Automatic programming is actually a euphemism for programming
with a higher-level language so that a solution could be given more
easily.
 There are some exceptions which have favorable properties:
 Relatively few parameters are involved.
 Many solutions are available.
 Explicit rules are known to select solutions.
 It is hard to generalize such special cases for the ordinary
software systems.
Readings in Computer Science: Software Engineering
NSB
31
Graphical programming
 Computer graphics, which has been applied successfully in other
fields, seems to be able to play a role in software design.
 Nothing convincing has ever emerged from this approach.
 The flowchart, considered as the ideal program-design medium, is a
very poor abstraction of software structure.
 The screens of today are too small to show detailed software diagrams.
 In its nature, software is very difficult to visualize.
Readings in Computer Science: Software Engineering
NSB
32
Program verification
 Program verification seems promising to avoid immense effort upon
implementation and testing by eliminating errors in the design
phase.
 No magic!
 Verifications are so much work that only a few programs have been verified.
 Verification cannot eliminate errors totally since mathematical proofs
can also be faulty.
 Specification, the baseline of verification, is usually incomplete and
inconsistent.
Readings in Computer Science: Software Engineering
NSB
33
Environments and tools
We have discussed this issue.
Readings in Computer Science: Software Engineering
NSB
34
Workstations
 More powerful computers surely facilitate
software development.
 But nowadays time of thinking, instead of waiting
for computers' response, is the dominant activity
of programmers.
Magical enhancement thus cannot be expected.
Readings in Computer Science: Software Engineering
NSB
35
Will the problem be
attacked in the future?
 The conceptual components of the task are now
taking most of time.
 We must consider those attacks that address the
essence of the software problem.
Readings in Computer Science: Software Engineering
NSB
36
Will the problem be attacked in
the future? --- Cont.
Well, there may be some copper bullets:
 Buy versus build
 Requirements refinement and rapid prototyping
 Incremental development
 Greater designers
Readings in Computer Science: Software Engineering
NSB
37
Buy versus build
 It is common practice to buy off-the-shelf products nowadays due to the
following reasons:

PC revolution has created many mass markets for software, which, together with
zero replication cost of software, stirred the motivation for software companies
to produce more and better software products.

Applicability of software is enhanced with the generalization of software tools
and the constantly decreasing hardware/software cost ratio.
Readings in Computer Science: Software Engineering
NSB
38
Requirements refinement
and rapid prototyping
 It is hardest to decide detailed technical requirements.
Unfortunately even the clients themselves do not exactly
know what they want.
 So iterative extraction and refinement of product
requirements are necessary.
Readings in Computer Science: Software Engineering
NSB
39
Requirements refinement and
rapid prototyping --- Cont.
 A client cannot specify completely, precisely, and correctly
the exact requirements of a modern software product
before trying some versions of the product.
 Rapid prototyping may give clients a first-hand feel of what
the product will be and a check for consistency and usability.
Readings in Computer Science: Software Engineering
NSB
40
Incremental development
 To develop software that has a comparable complexity as human
brain, a similar process should be followed, i.e. incremental
development.
 Advantages:
 The approach necessitates top-down design, thus allowing easy
backtracking and detecting fundamental defects as early as possible.
 An always working system stirs enthusiasm.
Readings in Computer Science: Software Engineering
NSB
41
Greater designers
 People is the key factor of solving problems.
 Steps have been taken to raise the level of our
practice from poor to good.
 Curricula
 Literature
 Research organizations
Readings in Computer Science: Software Engineering
NSB
42
Greater designers --- Cont.
 The proposed next step is to develop ways to grow great designers.
 Why?
 Creative minds present state-of-the-art works, the benefits of which are
order-of-magnitude compared with the average practices.
 How?
 Identify top designers as early as possible
 Assign a career mentor to be responsible for the development of the prospect
 Work out a career-development plan for each prospect
 Provide opportunities for designers to interact with and stimulate each other
Readings in Computer Science: Software Engineering
NSB
43
Readings in Computer Science: Software Engineering
NSB
44
Bullets towards NSB
1. We cannot abstract away the complexity without abstracting away the
essence?

“Divide and conquer” strategy

Is a hierarchical model of software possible?
We cannot always visualize software in hierarchical graphs?
2. The benefit of time-sharing is boundary?
3. The hardest single part of building a software system is deciding precisely
what to build?

How about design?
Readings in Computer Science: Software Engineering
NSB
45