What does it mean to be a test engineer?Andrii Dzynia
Test engineering is hard, even harder than software development. Being test engineer puts you in a wider context, with no clear boundaries. You have to find those by yourself. This requires courage. Courage to take action, courage to make mistakes. As a test engineer, you do mistakes every day. You do them so often that sometimes you feel you can predict the future. Scientific explanation to this phenomena is patterns recognition. It is an ability of our brain to match the information from a stimulus with information retrieved from memory. Defect prevention is hard. Together with technical skills one have to develop high social awareness. Working on safety nets never was so important, different types of checks on different levels to make sure software is reliable and serves its purpose to the variety of everyday use-cases. We know that life is so complex and sometimes complicated which makes it impossible to predict all possible outcomes and scenarios. But striving for excellence never was so important as nowadays in such an open, transparent and competitive environment.
Goal of my talk will be to show you my everyday job as a test engineer. Not only how to look for defects, but how to prevent them from happening. Not only how to automate tests(noun), but how to build safety nets to minimize end-user impact. Not only how to inform testing status but how to influence quality on company level.
Presented at DevClub.lv meeting http://devclub.lv/announcing-6th-devclub-lv
(video recording of talk is here http://devclub.lv/test-driven-development-tdd-why-and-how-raimonds-simanovskis) and at Agile Tour Vilnius 2013 conference (http://www.agileturas.lt/vilnius#raimonds_simanovskis).
What does it mean to be a test engineer?Andrii Dzynia
Test engineering is hard, even harder than software development. Being test engineer puts you in a wider context, with no clear boundaries. You have to find those by yourself. This requires courage. Courage to take action, courage to make mistakes. As a test engineer, you do mistakes every day. You do them so often that sometimes you feel you can predict the future. Scientific explanation to this phenomena is patterns recognition. It is an ability of our brain to match the information from a stimulus with information retrieved from memory. Defect prevention is hard. Together with technical skills one have to develop high social awareness. Working on safety nets never was so important, different types of checks on different levels to make sure software is reliable and serves its purpose to the variety of everyday use-cases. We know that life is so complex and sometimes complicated which makes it impossible to predict all possible outcomes and scenarios. But striving for excellence never was so important as nowadays in such an open, transparent and competitive environment.
Goal of my talk will be to show you my everyday job as a test engineer. Not only how to look for defects, but how to prevent them from happening. Not only how to automate tests(noun), but how to build safety nets to minimize end-user impact. Not only how to inform testing status but how to influence quality on company level.
Presented at DevClub.lv meeting http://devclub.lv/announcing-6th-devclub-lv
(video recording of talk is here http://devclub.lv/test-driven-development-tdd-why-and-how-raimonds-simanovskis) and at Agile Tour Vilnius 2013 conference (http://www.agileturas.lt/vilnius#raimonds_simanovskis).
Development without Testers: Myth or Real Option? (ConfeT&QA conference)Mikalai Alimenkou
Presentation from online conference ConfeT&QA (March 2012) about true role of testers and ways to fix development process to avoid their participation in usual stages of the quality control chain.
Can agile frameworks help small development teams? After looking at some agile basics, I examine two projects where a small development team used scrum. Agile can be used by small teams to their advantage with commitment and some work.
Presentation I did for the Orlando iOS Developer Meetup. It was originally intended to help those who were looking to build their first iOS applications, but turned into a presentation about good project management skills and how to manage your freelancing work.
Development without Testers: Myth or Real Option? (ConfeT&QA conference)Mikalai Alimenkou
Presentation from online conference ConfeT&QA (March 2012) about true role of testers and ways to fix development process to avoid their participation in usual stages of the quality control chain.
Can agile frameworks help small development teams? After looking at some agile basics, I examine two projects where a small development team used scrum. Agile can be used by small teams to their advantage with commitment and some work.
Presentation I did for the Orlando iOS Developer Meetup. It was originally intended to help those who were looking to build their first iOS applications, but turned into a presentation about good project management skills and how to manage your freelancing work.
Do you know EDD? EDD means Error Driven Development, aka “Write a test to reproduce the bug before fixing it”. That sentence leads the InfoJobs’ app to the zero bugs dream. And here are some slides to help me spread the idea to Schibsted’ teams.
Test-Driven Design (TDD) es una idea aparentemente simple: Escriba las pruebas para su código antes de escribir el código. Es "aparentemente simple" por que transforma el rol que testing juega en el proceso de desarrollo y cuestiona nuestros supuestos en la industria sobre el objetivo de testing. Testing ya no es solo acerca de evitar que los defectos lleguen al usuarios finales. Testing consiste en ayudar al equipo a entender las funcionalidad que los usuarios necesitan y hacer entrega de esas funcionalidad de forma confiable y productiva. Cuando TDD se sigue hasta sus últimas consecuencias, ocurren cambios radicales en la forma que desarrollamos software, la calidad de los sistemas que construimos mejora dramáticamente en términos de fiabilidad y flexibilidad en respuesta a nuevos requerimientos.
En esta charla:
• Los Administradores y Directores recibirán una justificación estratégica a nivel de negocios sobre TDD.
Some of the things I learned during the last years from the GURU of the AGILE manifesto.
Be a Clean Coder from Robert C. Martin
Be a Pragmatic Programmer from Andrew Hunt
Be a extreme Programmer from Kent Beck
Understand the Continuous Delivery from Jez Humble and David Farley.
Thanks to Bruno Bossola , Marcello Todori and Mario Romano for the good chats about this topics.
Test Driven Development Methodology and Philosophy Vijay Kumbhar
A technique for building software that guides software development by writing tests. This is the philosophy and state of mind that a developer should change and start following TDD
Fyrirlestur fyrir Félag tölvunarfræðinga og Verkfræðingafélagið þann 18.05.2022
Nýsköpun er forsenda tækniframfara sem eru forsendur framþróunar. Nýsköpun byrjar yfirleitt smátt og þarf margar ítranir til að virka. Frumkvöðlar sem eru að búa til nýjungar þurfa ekki einungis að glíma við tæknina og takmarkanir hennar, heldur einnig skoðanir og álit samtímamanna sem sjá ekki alltaf tilgang með nýrri tækni. Í þessum fyrirlestri skoðar Ólafur Andri nýsköpun og þær framfarir sem hafa orðið. Einnig skoðar hann hvert tækniframfarir nútímans muni leiða okkur á komandi árum.
Ólafur Andri Ragnarsson er aðjúnkt við Háskólann í Reykjavík og kennir þar námskeið um tækniþróun og hvernig tæknibreytingar hafa áhrif á fyrirtæki. Hann er tölvunarfræðingur (Msc) að mennt frá Oregon University í Bandaríkjanum. Ólafur Andri er frumkvöðull og stofnaði, ásamt fleirum, Margmiðlun og síðar Betware. Þá tók Ólafur Andri þátt í að stofna leikjafyrirtækið Raw Fury AB í Stokkhólmi.
Fyrirlestur haldinn fyrir tæknifaghóp Stjórnvísi þann 13. október 2020.
Undanfarna áratugi höfum við séð gríðalegar framfarir í tækni og nýsköpun á heimsvísu. Þessar framfarir hafa skapað mannkyninu öllu aukna hagsæld. Þrátt fyrir veirufaraldur á heimsvísu eru framfarir ekkert að minnka heldur munu bara aukast næstu árum. Gervgreind, róbotar, sýndarveruleiki, hlutanetið og margt fleira er að búa til nýjar lausnir og ný tækifæri. Framtíðin er í senn sveipuð dulúð og getur verið spennandi og ógnvekjandi í senn. Eina sem við vitum fyrir vissu er að framtíðin verður alltaf betri. Í þessu fyrirlestri ætlar Ólafur Andri Ragnarsson kennari við HR að fjalla um nýjustu tækni og framtíðina.
Technology is one of the factors of change. When new disruptive technology is introduced, it can change industries. We have many examples of that and will start this journey it one of the most important innovation that has come in our lifetimes, the smartphone. We will explore the impact of the smartphone and the fate of existing companies at the time when iPhone, the first smartphone as we know them, was introduced to the world.
We will also look at other examples from history. Then we look at the broader picture, past industrial revolutions and the one that we are experiencing now, the fourth industrial revolution. Specifically we look briefly at the technologies that fuel this revolution, for example artificial intelligence, robotics, drones, internet of things and more.
Manlike machines have fascinated humans since ancient times. The modern robots start to take shape with the industrial revolution. In the 20th century robots were mostly industrial machines you would see in factories, like car factories.
Today, robots can have sensors, vision, they can hear and understand. They can connect to the cloud for more information. However, we are still in the early stages of robotics and robots will need to go a long way to become useful as a ubiquitous general purpose devices.
The normal interaction with computers is with keyboard and a mouse. For display a rectangular somewhat small screen is used with 2D windowing systems. The mouse was invented more the 40 years ago and has been for 20 years dominant input. Now we are seeing new types of input devices. Multi-touch adds new dimensions and new applications. Natural user interfaces or gesture interfaces where people point to drag objects. Computers are also beginning to recognize facial expressions of people, so it knows if you are smiling. Voice and natural language understanding is getting to a usable stage. All this calls all types of new applications.
Displays are getting bigger. What if any surface was a screen? If you could spray the wall with screen? Or have you phone project images to the wall.
This lectures explores some of these new types of interactions with computers and software. It makes the old mouse look old.
Local is the Lo in SoLoMo, the buzz word. Local is not only about location, it's also about your digital track record. Over 70% of Netflix users watch the films recommend. Mining data to understand people's behaviour is getting to be a huge and valuable business. Advertisers see opportunities in getting direct to their target groups. Predictive intelligence is also about where you will be at some time in the future, and where somebody you know will be.
It turns out that Facebook and Google know you better than you think you know yourself. The world is about to get really scary.
Over two billion people signed up for Facebook. This site the most used site for people when using the Internet. People are not watching TV so much anymore - they using Facebook, Youtube and Netflix and number of popular web sites.
Some people denote their time working for others online. What drives people to write an article on Wikipedia? They don´t get paid. Companies are enlisting people to help with innovations and sites such as Galaxy Zoo ask people to help identifying images. And why do people have to film themselves singing when they cannot sing and post the video on Youtube?
In this lecture we talk about how people are using the web to interact in new ways, and doing stuff.
With the computer revolution vast amount of digital data has become available. With the Internet and smart connected product, the data is growing exponentially. It is estimated that every year, more data is generated than all history prior. And this has repeated over several years.
With all this data, it becomes a platform for something new of its own. In this lecture, we look at what big data is and look at several examples of how to use data. There are many well-know algorithms to analyse data, like clustering and machine learning.
After the computing industry got started, a new problem quickly emerged. How do you operate this machines and how to you program them. The development of operating systems was relatively slow compared to the advances in hardware. First system were primitive but slowly got better as demand for computing power increased. The ideas of the Graphical User Interfaces or GUI (Gooey) go back to Doug Engelbarts Demo of the Century. However, this did not have much impact on the computer industry. One company though, Xerox, a photocopy company explored these ideas with Palo Alto Park. Steve Jobs of Apple and Bill Gates of Microsoft took notice and Apple introduced first Apple Lisa and the Macintosh.
In this lecture on we look so lessons for the development of software, and see how our business theories apply.
In this lecture on we look so lessons for the development of algorithms or software, and see how our business theories apply.
In the second part we look at where software is going, namely Artificial Intelligence. Resent developments in AI are causing an AI boom and new AI application are coming all the time. We look at machine learning and deep learning to get an understanding of the current trends.
We are currently living in times of great transformation. We have over the last couple of decade seen the Internet become the most powerful disrupting force in the world, connecting everyone and transforming businesses. Now everyday objects - things we use are getting smart with sensors and software. And they are connecting. What does this mean?
We will see the world become alive. Cars will talk to road sensors that talk to systems that guide traffic. Plants will talk to weather systems that talk to scientists that research climate change. Farming fields will talk to the farming system that talks to robots that do fertilising and harvesting. Home appliances like refrigerators, ovens, coffee machines and microwaves ovens will talk to the home food and cooking system that will inform the store that you are running out butter, cheese, laundry detergent and coffee beans, which will inform the robot driver to get this to your house after consulting your calendar upon when someone is at home.
In this lecture we explore the Internet of Things, IoT.
The Internet grew out of US efforts to build the ARPANET, a network of peer computers built during the cold war. The two major players were military and academia. The network was simple and required no efforts for security or social responsibility. The early Internet community was mainly highly educated and respectable scientist. In the early 1990s the World Wide Web, a hypertext system is introduced, and soon browsers start to appear, leading the commercialization of Net. New businesses emerge and a technology boom known as the dot-com era.
The network, now over 40, is being stretched. Problems such as spam, viruses, antisocial behaviour, and demands for more content are prompting reinvention of the Net and threatening its neutrality. Add to this government efforts to regulate and limit the network.
In this lecture we look at the Internet and the impact of the network. We will also look at the future of the Internet.
The Internet grew out of US efforts to build the ARPANET, a network of peer computers built during the cold war. The two major players were military and academia. The network was simple and required no efforts for security or social responsibility. The early Internet community was mainly highly educated and respectable scientist. In the early 1990s the World Wide Web, a hypertext system is introduced, and soon browsers start to appear, leading the commercialisation of Net. New businesses emerge and a technology boom known as the dot-com era.
The network, now over 40, is being stretched. Problems such as spam, viruses, antisocial behaviour, and demands for more content are prompting reinvention of the Net and threatening its neutrality. Add to this government efforts to regulate and limit the network.
In this lecture we look at the Internet and the impact of the network. We will also look at the future of the Internet.
The ideas for cellular phones were developed in the 1940s. However, it was not until the microprocessor becomes available that practical commercial solutions are possible.
Today there are more than 5 billion unique mobile phone subscriptions in the world and of them about 2.5 billion are smartphones. This device is so powerful that people check it over 40 times a day.
In this lecture we look mobile. We also look at the history of communication since the telegraph and how the mobile market developed in the 80s and 90s until the iPhone was released in 2007. That same year Western Union stopped sending telegraph messages.
Did you know that the term "Computer" once meant a profession? And what did people or computers actually do? They computed mathematical problems. Some problems were tedious and error prone. And it is not surprising that people started to develop machines to aid in the effort. The first mechanical computers were actually created to get rid of errors in human computation. Then came tabulating machines and cash registers. It was not until telephone companies were well established that computing machines became practical.
First computers were huge mainframes, but soon minicomputers like DEC’s PDP started to appear. The transistor was introduced in 1947, but its usefulness was not truly realized until in 1958 when the integrated circuit was invented. This led to the invention of the microprocessor. Intel, in 1971, marketed the 4004 – and the personal computer revolution started. One of the first Personal Computers was MITS’ Altair. This was a simple device and soon others saw the opportunities.
In this lecture we start our coverage of computing and look at some of the early machines and the impact they had.
Software is changing the way traditional business operate. People now have smartphones in their pockets - a supercomputer that is 25,000 times more powerful and the minicomputers of the 1960s. This is changing people's behaviour and how people shop and use services. The organisational structure created in the 20th century cannot survive when new digital solution are being offered. Software is changing the way traditional business operate. People now have smartphones in their pockets - a supercomputer that is 25,000 times more powerful and the minicomputers of the 1960s. This is changing people's behaviour and how people shop and use services. The organisational structure created in the 20th century cannot survive when new digital solution are being offered. The hierarchical structure of these established companies assumes high coordination cost due to human activity. But when the coordination cost drops
The organisational structure that companies in the 20th century established was based on the fact that employees needed to do all the work. The coordination cost was high due to the effort and cost of employees, housing etc. Now we have software that can do this for use and the coordination cost drops to close-to-zero. Another thing is that things become free. Consider Flickr. Anybody can sign up and use the service for free. Only a fraction of the users get pro account and pay. How can Flickr make money on that? It turns out that services like this can.
Many businesses make money by giving things away. How can that possibly work? The music business has suffered severely with digital distribution of content. Should musicians put all their songs on YouTube? What is the future business model for music?
One of the great irony of successful companies is how easily they can fail. New companies are founded to take advantage of some new technology. They become highly successful and but when the technology shifts, something new comes along, they are unable to adapt and fail. This is the innovator’s dilemma.
Then there are companies that manage to survive. For example, Kodak survived two platform shift, only til fail the third. IBM has survived over 100 years. What do successful companies do differently?
History has many examples of great innovators who had difficult time convincing their contemporaries of new technology. Even incumbent and powerful companies regarded new technologies as inferior and dismissed it as "toys". Then when disruptive technologies take off they often are overhyped and can cause bubbles like the Internet bubble of the late 1990s.
In this lecture we look at some examples of disruptive technologies and the impact they had. We look at the The Disruptive Innovation Theory by Harvard Professor Clayton Christensen.
Technology evolves in big waves that we call revolutions. The first revolution was the Industrial revolution that started in Britain in 1771. Since than we have see more revolutions come and how we are in the fifth. These revolutions follow a similar path. First there is an installation period where the new technologies are installed and deployed, creating wealth to those who were are the right place at the right time. This is followed by a frenzy, where financial markets wants to be apart. The there is crash and turning point, followed by synergy, a golden age.
In 1908, a new technological revolution started. It was the Age of Oil and Automobile. The technology trigger was Henry Ford´s new assembly line technique that allowed the manufacturing of standardized, low cost automobile. This created the car industry and other manufacturing companies. This also created demand for gas thus creating the oil industry. During the Roaring Twenties the stock prices rose to new levels, until a crash and the Great Depression. Only after World War II, came a turnaround point followed by a golden age in the post-war boom.
In this lecture we look at a framework for understanding technological revolutions. There revolutions completely change societies and replace the old with new technologies. We will explore how these revolutions take place. We should now be in the golden age phase.
We also look at generations.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
In the early days of product development, the technology is inferior and lacking in performance. The focus is very much on the technology itself. The users are enthusiast who like the idea of the product, find use for it, and except the lack of performance. Then as the product becomes more mature, other factors become important, such as price, design, features, portability. The product moves from being a technology to become a consumer item, and even a community.
In this lecture we explore the change from technology focus to consumer focus, and look at why people stand in line overnight to buy the latest gadgets.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
3. Agenda
KISS
DTSTTCPW
YAGNI
WIIFM
DRY
OAOO
GEFN
RDUF
JED
FFwd
Fake it ‘til you make it
Red/Green/refactor
mantra
Continuous
Integration
4. KISS
Keep It Simple Stubid!
Focus on simplicity
– Quick, easy, least integrating parts
– Avoid over-engineering
– Drop anything that takes too long
5. DTSTTCPW
Do The Simplest This That Could Possibly Work
Then refactor and refine
6. YAGNI
You Aren’t Gonna Need It
Deliver only what is asked, no more, no less
7. WIIFM
What’s In It for Me
Put yourself in the shoes of the stakeholder and
ask this question
– Then justify any features planned
8. DRY
Don’t Repeat Yourself
Anything – just avoid duplication
Duplication is a waste, promotes error, and
results in maintenance problems
9. OAOO
Once And Only Once
A variant for DRY with human input
Automate repetitive tasks – testing, build,
deployment
Use scripts - automate
10. GEFN
Good Enough For Now
The goal is not to archive perfect state but to
reach a working stage at the end of each
iteration
Each iteration should build on the output of the
previous one and should leave your application
on an better stage than before
11. RDUF
Rough Design Up Front
Come up with high-level design to provide
guidelines for initial iterations
Then improve on the previous iterations
12. JED
Just Enough Documentation
Less is more
Document what you know – not what you want
or intent to know
Document early and often
13. FFwd
Fail Forward
Catch mistakes early
Mistakes should be small and easy to correct
14. Fake it ‘til you make it
Use Mock Objects
Test Driven development
15. Red/Green/Refactor mantra
In TDD you write test classes before
implementation code
First it will be red, the fix it to become green
16. Continuous Integration
Whenever a developer commits his changes, it
automatically triggers a build process
This allows you to check immediately if it caused
a build to break
Reduces integration hell
Goal is to have deliverable software at any point
17. Summary
KISS
DTSTTCPW
YAGNI
WIIFM
DRY
OAOO
GEFN
RDUF
JED
FFwd
Fake it ‘til you make it
Red/Green/refactor
mantra
Continuous
Integration
