1. © Yuriy Guts, 2013

2. What do we actually do?

3. Myth #1
Our job is to operate computers

4. Computer is merely
a helper tool in
programming
Programmers can even
weave cloth!
(Google: Jacquard Loom)

5. Myth #2
Machines can think

6. Not quite yet.
They do only what they re told to do.
Our job:
Describe absolutely precisely
what to do

7. We have to speak
the same language
For computers, this
language is numbers

8. Example:
How to tell the computer
to add 19+23?
160
16
1
138
30
17
1
2
195
162
18
1
180
76
205
33
19
23
(Intel 80386, MS-DOS, .COM)

9. Fact:
Modern software consists of
MILLIONS of instructions

10. Is there a simpler way?!

11. Let s create a more human-readable language
and let the computer translate it to numbers
.model
tiny
start:
.386
mov
al,
num1
mov
bl,
num2
.data
add
al,
bl
num1
db
19
mov
sum,
al
num2
db
23
sum
db
?
mov
ah,
4ch
int
21h
.code
org
100h
end
start

12. How is THAT simpler?!

13. To make things easier,
we must abstract away from unimportant details
This is why new technologies appear
They allow us to focus on some details
and ignore others

14. Example (Python):
How to tell the computer
to add 19+23?
print
19
+
23

15. That s way better

16. Some famous abstractions
Databases
How to ensure efficient and reliable storage?
How to search and edit data conveniently?
Networks
How to make machines collaborate?
How to split difficult tasks among multiple machines?

17. Myth #3
It’s a boring and tedious job

18. An engineer is concerned with applying scientific
knowledge and ingenuity to develop solutions for
technical, social and economic problems.
Ingenuity — [Wiki] The quality of being clever, original,
and inventive, often in the process of applying ideas to
solve problems or meet challenges.
Code is only an end result.
A good engineering design is comparable to art.

19. Types of software
(by means of access)
Desktop Web
Mobile Embedded

20. Desktop
Software for workstations and laptops
Examples
• Adobe Photoshop
• Microsoft Office
• “Heavy” 3D games
Specifics
• Rich hardware capabilities
• Many applications already have
online alternatives

21. Web
Software accessible over the Internet
Examples
• Facebook
• Wikipedia
• Google Search
Specifics
• Distributed nature
• Many simultaneous users
• Unified access from many devices

22. Mobile
Software for handheld consumer devices
Examples
• Instagram
• Foursquare
• iBooks
Specifics
• Energy-efficiency, limited capabilities
• Sensors: GPS, gyro, accelerometer, ...
• Large family of devices and sizes

23. Embedded
Specialized device-specific integrated software
Examples
• Medical devices
• Airplane “black boxes”
• Security systems
Specifics
• Limited user interaction
• Low-level programming
• Speed and reliability constraints

24. Popular programming languages
(as of Q1 2013)
Java C#
JavaScript Objective-C
C++ Python
PHP Ruby
Functional (Scala, Haskell, Erlang, Lisp family...)

25. Myth #4
Learning the right language
will make you a good professional
Every language is a tool,
know when to use it

26. Learning and switching

27. Types of IT professionals
System Analysts Project Managers
Software Architects Technical Writers
Software Developers System Administrators
QA Engineers Support Engineers

28. Software development lifecycle
Requirement analysis + user experience prototyping
Choice of technology stack & architecture
Design and implementation
Quality assurance and monitoring
Deployment
Maintenance and support iterative

29. Q&A
yuriy.guts@eleks.com