Video and slides synchronized, mp3 and slide download available at URL http://bit.ly/1fjTxvB. Trisha Gee and Todd Montgomery attack the technology industry’s sacred cows by exposing the motivations that hide behind them. They discuss how these motivations lead us into practices that hinder rather than help us deliver quality software. Also, they discuss why some organisations seem to be achieving things that the traditional corporate IT departments can only dream of. Filmed at qconnewyork.com. Todd Montgomery is Ex-NASA researcher, Chief Architect at Kaazing. Trisha Gee is Java Champion and Engineer.

1. How did we end up here?
Trisha Gee - @trisha_gee
Todd Montgomery - @toddlmontgomery
Shout out: Martin Thompson - @mjpt777

2. InfoQ.com: News & Community Site
• 750,000 unique visitors/month
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Portuguese)
• Post content from our QCon conferences
• News 15-20 / week
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Watch the video with slide
synchronization on InfoQ.com!
http://www.infoq.com/presentations
/technology-industry-motivation

3. Presented at QCon New York
www.qconnewyork.com
Purpose of QCon
- to empower software development by facilitating the spread of
knowledge and innovation
Strategy
- practitioner-driven conference designed for YOU: influencers of
change and innovation in your teams
- speakers and topics driving the evolution and innovation
- connecting and catalyzing the influencers and innovators
Highlights
- attended by more than 12,000 delegates since 2007
- held in 9 cities worldwide

8. How bad can things really be?

9. Successful Challenged Failure
Ad-hoc 49% 37% 14%
Iterative 61% 28% 11%
Agile 60% 28% 12%
Traditional 47% 36% 17%
Software Project Success Rates
- Dr Dobbs 2010

10. < 10 11 - 25 > 25
Ad-hoc 70% 58% 40%
Iterative 88% 68% 55%
Agile 83% 70% 55%
Traditional 69% 51% 50%
Software Project Success Rates – by Team
Size
- Dr Dobbs 2010

11. Well that‟s the
optimistic view!

12. Successful: 32%
Challenged: 44%
Failure: 24%
– Standish Group Chaos Report 2010
Software Project Success Rates

13. < $350,000: 20%
$350,000 - $1,000,000: 25%
> $1,000,000: 28%
– Gartner 2012
Software Project Failure Rates

14. In a study of over 5400 large scale
projects (> $15m)
17% go so badly that they threaten
the existence of the company
undertaking them
– The McInsey Group with Oxford University 2012

15. Sacred Cows - It’s BBQ Time!!!

16. Enterprise Software

17. ent•ter•prise
noun ˈen-tə(r)-ˌprīz
: a project or activity that involves many
people and that is often difficult
: the ability or desire to do dangerous or
difficult things or to solve problems in
new ways
Source: http://www.merriam-webster.com/

18. Naming Matters !!!

21. Product Management

22. Minimum Viable Product ?

23. Product Owner ?

25. Technologists ARE
part of the business

26. Take responsibility for ROI

27. How can I get an answer for the
minimum investment?

28. Agile Methods

31. Water-scrum-fall

32. What really matters?

33. Need to focus on learning,
feedback cycles,
and outcomes

34. There is an uncomfortable
truth…

35. “What would have been different
if you were not involved?”

36. Shared Mutable State

37. “…Shared Mutable State...”
the most feared words in
computing

38. …if not they should be!

41. Shared Mutable State
should only be used for
systems programming

42. Embrace append-only,
single writer,
and shared nothing designs

43. If you don‟t...
math will hunt you down and
there is nowhere to hide!

44. Universal Scalability Law
0
2
4
6
8
10
12
14
16
18
20
1 2 4 8 16 32 64 128 256 512 1024
Speedup
Processors
Amdahl USL

45. Be ruthless in reducing
complexity

46. Text Encoding

48. But it‟s human readable...

49. Binary is hard to work with...

52. Big Data

53. Communications
Battery life and bandwidth?

54. Synchronous Comms

55. Bad things will happen!!!

56. Synchronous Communication
is the crystal meth of
distributed programming

57. Causes a coupling in
location and time

58. Errors need to be
first class messages

59. Are your micro services
on crystal meth?

60. Abstraction

61. “All non-trivial abstractions,
to some extent, are leaky.”
- Joel Spolsky

62. “The detail of underlying
complexity cannot be ignored.”

63. “the purpose of abstracting
is not to be vague, but to create
a new semantic level in which
one can be absolutely precise”
- Dijkstra

64. We could say the main issue is
that people don‟t understand
abstractions...but...

65. Sins committed in the name of
Abstraction

66. ORMs !!!

67. Functional Programming

68. What is the biggest issue with
functional programming?

69. Functional Programmers

70. Functional programming is
NOT
the answer to multi-core

71. Software Transactional Memory
was a failed experiment!

72. Universal Scalability Law
0
2
4
6
8
10
12
14
16
18
20
1 2 4 8 16 32 64 128 256 512 1024
Speedup
Processors
Amdahl USL

73. No Mechanical Sympathy?

74. However there is
genuine brilliance in
functional programming

75. Collaborate and great things
can happen...

76. Throw hardware at it…
development is too
expensive

77. The free lunch is over…
we cannot be sloppy anymore…

78. Code must be simple
and composable

79. Cache Sub-System
L1(D) - 32K
L2 - 256K
L3 – 8-20MB
LF/WC
Buffers L1(I) – 32K
L0(I) – 1.5k µops
32 Bytes / cycle
System Agent
TLB
Pre-fetchers
TLB
Pre-fetchers
128 bits / cycle
MOB
Memory
Controller
QPI
QPI Bus
Memory
Channels
16 Bytes / cycle
Ring Bus
PCI-e
Controller
32 Bytes / cycle 32 Bytes / cycle

80. Patterns of access and locality
are key to performance

81. Accumulated
Improvement
Time
Bandwidth
Latency
Memory Sub-System Performance

82. Accumulated
Improvement
Time
Network
Bandwidth
Response Time
Storage
Capacity
CPU Cores
Memory
Capacity

83. What does this mean for
software?

85. Think in terms of transformation
and flow of data – not code!

86. Diversity

87. Testosterone Driven Development

89. What did the
Carnegie Mellon studies show?

92. Fake it until you make it…

93. “As soon as you realise that most
people don‟t know what they are doing
the world makes a lot more sense…”
– Farley’s second law

94. We need to look seriously at
training programmers

95. Coaching and Apprenticeships

96. “The most important thing I've
accomplished, other than building
the compiler, is training young
people.”
- Grace Hopper

97. “'Do you think we can do this?' I
say, „Try it.‟ And I back 'em up.
They need that. I keep track of
them as they get older and I stir
'em up at intervals so they don't
forget to take chances.
- Grace Hopper

98. In closing…

99. What are the
greatest achievements
of the human race?

100. The Scientific Method

101. Understanding of Evolution

102. Don‟t feel bad…
We are living in the era of
Software Alchemy

104. Questions?
@trisha_gee – Trisha Gee
@toddlmontgomery – Todd Montgomery
@mjpt777 – Martin Thompson
“It does not matter how intelligent you are, if you
guess and that guess cannot be backed up by
experimental evidence –
then it is still a guess.”
- Richard Feynman

105. Watch the video with slide synchronization on
InfoQ.com!
http://www.infoq.com/presentations/technology
-industry-motivation