T +30 6938 119424 y.kanellopoulos@sig.eu www.sig.eu

Startup Founder 101: IT Strategy for Startups Yiannis Kanellopoulos: SIG, Practice Leader Greece - ID-GC, Core Member Twitter: @ykanellopoulos

12/02/2014

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Outline

•  About SIG •  Why software is important •  Aspects of IT Strategy •  Managing Your Product’s Quality

•  Appendix •  Examples •  Supporting Material/References

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Who we are: Spin-off of CWI and University of Amsterdam

Headquarters

…since 2010

2000 - 2005 2005 - 2010

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We live in interesting times

“There has never been a worse time to be competing with machines, but there has never been a better time to be a

talented entrepreneur” Erik Brynjolfsson, Andrew McAfee: Race Against the Machine

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Software is …

… the DNA of today’s

information Society

… eating the world

Prof. Dr. Ing. Joost Visser, SIG Head

of R&D

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Software can be an expensive failure

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… in the corporate

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… as well as the startup world

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The Bermuda triangle for developing your Product

Process

Methodology People

Product Developers

(internal + external)

Testing

Agile

Requirements Elicitation

Deployment

Co-founders (technical + non-technical)

Software Vendors Lean Startup

Kanban

Development

Extreme Programming

Scrum VCs

ISO 25010

Technology Selection

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People – Forming your team: Internal development is less risky

Internal development

Appropriate when there is internal expertise on how

to build your Product

Overall control over product

Priority is given to agree upon technology and

methodology of working

Outsourcing/External

development Appropriate when there is no or limited expertise to

build your product

Moderate control over vendor

Limited control over product

Priority is given to control the deliverable of the

vendor/external developer

Offshoring (India/China)

Appropriate when the lowest cost is a priority

Almost no control over vendor and product

Priority is given to establish communication with

vendor

Moderate Risk High Risk Very High Risk

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Methodology selection: Basic principles for developing your Product

Product has to be developed jointly between IT and non-technical people: •  Non-technical provide the requirements and IT translates them into code •  Both need to validate requirements and agree upon their prioritisation •  Both need to test the Product, non-technical its functional suitability, IT its technical

Technical and non-technical people need to find a common language to understand each other: •  Avoid jargon •  Explain consequences of requirements in terms of costs (i.e. time, money) and expected

value •  Learn to discuss requirements/algorithms using pseudo-code

Develop Product in increments: •  Agree upon the core functionality (MVP) that needs to be implemented in first place •  Improve Product in continuous increments (i.e. bi-weekly, monthly) •  Form a plan with the main theme of each increment

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Think Analytically: Pseudocode describing how to make coffee

Repetition structure

Selection structure

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Process – Development: Each technology has its pros and cons

Technology ✔ ✖ .NET C# Enhances Productivity High productivity can also be a project risk

Objective-C Maximises user experience on iOS devices Inherits legacy C’s features that create reliability and maintainability risks

Java Safe choice A safe technology choice does not guarantee project success

PHP Easy to learn Non-suitable for large and critical web applications

Python Easy programming which allows developers to build applications that scale quickly

Complicated library landscape leads to higher development and maintenance costs

Ruby Developers tend to like it Hard-to-fix bugs and longer development time through over-use of language features

SAP Functionality ready to be used based on industry’s best practices

Custom code decreases the value of the system

Source: SIG website, www.sig.eu - News and publications: Technology Risk Reviews

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Maintainability

Jan 2011 Apr 2011 Jul 2011 Oct 2011 Jan 2012 Apr 2012 Jul 2012 Oct 2012 Jan 20130.000.250.500.751.001.251.501.752.002.252.502.753.003.253.503.754.004.254.50

Product: Good quality builds trust

target

Target for system’s technical quality as

imposed by the Board of Directors of large

insurance company to their IT department.

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Product: Good quality means less costs in the future

Init Build Accept Evolution

(Maintenance and Support)

Functional quality: Does the product meet the current user needs?

Software Product Quality • What is the expected lifetime of the product? • Can the product be changed easily? • What are the costs of evolving this product?

20% of *lifecycle cost 80% of *lifecycle cost

* The baseline for lifecycle cost calculations is 10-15 years

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An analogy of a software product

Team Formation = System Design

Team Players = System

Components

Footballers = Units of the system. They are being evaluated by a

set of physical attributes

Lines of the Formation = System Components

Lines of the Formation = System Components

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System Components: Your product should not have more than 7-9

The characteristics that a maintainable and balanced system should have, are:

•  The number of components: should be between 7-9

•  The relative size of components: should be of comparable size

all changes located in a single large component

most changes located in a single large component

changes can be located in one of many components

changes located in a small number of components of limited scope

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Unit Complexity

How we define complexity •  Number of decision points per unit (method/function) •  McCabe, IEEE Transactions on Software Engineering, 1976

Method

McCabe: 4

Complexity Risk Profile

1-10 Clear code, small risk

11-20 Complex, medium risk

21-50 Very complex, high risk

> 50 Not understandable, untestable, very high risk

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Unit Size

Unit size •  A unit is a method, procedure or function (depending on technology) •  Smaller units can more easily be reused •  Smaller units have lower complexity •  Smaller units can more easily be documented via their name

Size of the unit (lines of code)

Risk Profile

1-20 Easy to understand, no risk

21-50 Fairly complex, low risk

51-100 Complex, medium risk

> 100 Very complex code, high risk

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Duplication

Duplication of code reduces maintainability •  Substantial duplication implies high maintenance costs. •  Substantial duplication makes bugfixing harder. •  Substantial duplication makes testing harder.

0: abc 1: def 2: ghi 3: jkl 4: mno 5: pqr 6: stu 7: vwx 8: yz

34: xxxxx 35: def 36: ghi 37: jkl 38: mno 39: pqr 40: stu 41: vwx 42: xxxxxx

14 lines duplicated 7 lines redundant

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Questions?

Yiannis Kanellopoulos y.kanellopoulos@sig.eu

http://www.sig.eu +30 6938 119424 @ykanellopoulos

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Example: Complex and badly architected system

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Examples of implemented architectures

A

B

C D

E F

D

A

C

B

D

E F G

Good Example

Bad Example

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Example: Complex Method

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2,259 lines later

è

Example: Long Method

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Vision of SIG

Software is the DNA of our modern information society •  Invisible to most •  Overwhelmingly complex •  Largely determines how businesses, governments, and individuals perform

Software product measurement is key for mastering information technology •  Further professionalize providers of information systems •  Provide client organizations with control over quality, costs, risks •  Increased transparency allows better functioning IT marketplace

Greece •  SIG wants to make modest, but structural contribution to economic transformation •  Through business development and joint research

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Software Improvement Group

Why clients hire us We help organisations to be in control over their software. As we yearly analyze more than 500 software systems, we know how to advise our clients to get the best out of their IT investments.

Activity

Management advisory, fact-based Accredited software analysis lab employs analysis tools and models Experienced staff transforms analysis data into advice

Track record

Finance, government, logistics, telecom, manufacturing, energy, …

“We translate detailed technical findings about software-intensive systems into actionable information for top management”

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Software Analysis Laboratory Key numbers

Monitoring: •  550+ systems, concurrently •  27 mln+ lines of code per week •  50+ technologies •  100+ events per week •  30+ monitor alerts per week

Benchmark: •  750+ systems •  22,000 snapshots •  160 mln+ lines of code •  100+ technologies •  3 bln+ lines of code analyzed

Software Analysis Toolkit

Pre-production database

Production database

Source code upload

Benchmark database

Satisfies sanity

checks?

File storage

Upload received

properly?

Statistical analysis

Improvements to

Significant changes?

Wait for new

Yes

No

No

Yes Yes

Yes

Monitor alert

Event Event

Analysis and feedback

No

Look at website

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Experience stems from the corporate world

In Europe In Greece

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Services

Software Risk Monitoring

Software Risk Assessment

•  Continuous measurement, feedback, and development consultancy •  Quality assurance during the entire product lifecycle

•  In-depth investigation of software quality and associated business risks •  Answers to specific research questions

Software Product Certification •  Five levels of technical quality (maintainability) •  Evaluation by SIG, certification by TÜV Informationstechnik

Portfolio Analysis and Optimisation •  Combining technical analysis and application lifecycle information •  Supporting portfolio evolution decisions with a sustainable roadmap

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How to manage Software Product Quality: ISO 25010

Software Product Quality

ISO 25010

Functional Suitability

Performance Efficiency

Compatibility

Usability Reliability

Security

Maintainability

Portability

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Elements on measuring Product’s technical quality

See: www.sig.eu/en/certification for more information.

Volume

Duplication

Unit size

Unit complexity

Unit interfacing

Module coupling

Component balance

Component independence

Analysability X X X X

Modifiability X X X

Testability X X X

Modularity X X X

Reusability X X

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Effects of Software Product Quality (1/2) Higher quality software is built cheaper

•  Higher quality software has a better design, requires less rework, can be tested more cost-

effectively, and is easier to change when requirements change •  Higher quality software requires smaller teams with less overhead •  (Source: SIG Benchmark data of systems built using Java or .net)