- Template parameter and auto type inference.
- Auto refenerces and passing arguments into a function.
- Expression categories: (gl|r|l|x|pr)-values.
- When are constructors get called and when do not.
- Tail recursion optimisation becomes possible in C++.
- Actually, std::move does not move anything.
- Constexpr vs. const.
- Smart pointers vs. raw pointers.
- Function objects and lambdas.
- Case study: asyncronous notifier.
- Case study: write-only replicable storage.

- Template parameter and auto type inference.
- Auto refenerces and passing arguments into a function.
- Expression categories: (gl|r|l|x|pr)-values.
- When are constructors get called and when do not.
- Tail recursion optimisation becomes possible in C++.
- Actually, std::move does not move anything.
- Constexpr vs. const.
- Smart pointers vs. raw pointers.
- Function objects and lambdas.
- Case study: asyncronous notifier.
- Case study: write-only replicable storage.

C++ is no longer C with classes and it never was only an Object Oriented language. C++ is a general-purpose programming language. It has imperative, object-oriented and generic programming features, while also providing facilities for low-level memory manipulation. If used correctly, it provides hard to beat performance. Such usage requires a good knowledge of C++ templates and Modern C++ Idioms which are much different from commonly known design patterns popularized by GoF book and invented to handle common use cases in pure OO languages like Java or C#.

What you will learn: During the workshop, we will refresh and broaden our knowledge about C++ templates and will learn Modern C++ Idioms. Crafting those skills will allow us to build powerful tools that are useful in the everyday work of every C++ developer.

Experience required: In order to be able to follow the workshop, you should be current with C++ and have some recent experience with writing simple C++ templates. C++11/14 knowledge is suggested but not mandatory.

Environment: A laptop with a relatively new C++ compiler. It is recommended to have the latest version of one of the compilers (Visual Studio, gcc or clang).

Language: English.

Idioms to be covered (plan):
- Non-Copyable
- RAII
- Copy-and-swap
- Smart Pointer
- Type Traits
- Tag dispatch
- Policy-based design
- EBO
- Type Erasure
- SOO
- Copy-on-write
- CRTP
- Singleton

C++ is no longer C with classes and it never was only an Object Oriented language. C++ is a general-purpose programming language. It has imperative, object-oriented and generic programming features, while also providing facilities for low-level memory manipulation. If used correctly, it provides hard to beat performance. Such usage requires a good knowledge of C++ templates and Modern C++ Idioms which are much different from commonly known design patterns popularized by GoF book and invented to handle common use cases in pure OO languages like Java or C#.

What you will learn: During the workshop, we will refresh and broaden our knowledge about C++ templates and will learn Modern C++ Idioms. Crafting those skills will allow us to build powerful tools that are useful in the everyday work of every C++ developer.

Experience required: In order to be able to follow the workshop, you should be current with C++ and have some recent experience with writing simple C++ templates. C++11/14 knowledge is suggested but not mandatory.

Environment: A laptop with a relatively new C++ compiler. It is recommended to have the latest version of one of the compilers (Visual Studio, gcc or clang).

Language: English.

Idioms to be covered (plan):
- Non-Copyable
- RAII
- Copy-and-swap
- Smart Pointer
- Type Traits
- Tag dispatch
- Policy-based design
- EBO
- Type Erasure
- SOO
- Copy-on-write
- CRTP
- Singleton

And we will build our own CI with conan and travis
Introduction
Developers’ mind has a common opinion, about their work which become completed after they’ve committed the code, and what happens next – not their problem. There is a great quote by Robert Highline for that thesis:
Each person should know how to change diapers, plan the invasion, harvest a pig, construct buildings, control a ship, write sonnets, make financial reports, build walls, set bones, assist dying, carry out an order, give out orders, cooperate, act alone, solve equations, analyze new problems, fertilize plants, program computers, cook tasty food, fight with dignity, die with dignity.

Specialization is the destiny of insects.

And instead of the opinion mentioned above, will put out our own thesis - the fact that code compilates on the developer’s environment and developer’s personal machine is not interesting for anyone! Our goal - Ii to make another step to the continuous integration, automate dependency resolution, assembling and unit testing for all the platforms which are interesting for us.

Continuous Integration
Continuous integration is the kind of practice, according to which, developers periodically (you can read it as daily) put out the results of the work into the main code branch. First use of that practice was introduced in the Buch method. Later, at extreme programming methodology, it improved with automatic unit tests run. Next step of current practice development is Continuous Delivery - the process where the distributive is created, after all acceptance tests are successfully completed, the distributive which ready to be published to the customer. And at the very end we can speak about Continuous Deployment during which all the changes that passed the testing phase successfully, automatically deployed to production. If you are already confused, you can imagine the following sequence:
1. Continuous integration
2. Continuous delivery
3. Continuous deployment
At the course of the current master-class we will speak about CI in the scope of C++ development.

Preliminary requirements
What is required from you:
- experience in using C++ (thanks, Cap!)
- laptop with any OS installed
- one of the compilers (Visual Studio >= 2015 / g++ >= 5.4 / clang++ >= 3.9 / Xcode >= 8.0)
- cmake >= 3.6 (you need to understand the syntax of CMakeLists.txt)
- git >= 2.10
- python >= 3.5
- pip3 >= 9.0
- github.com account
- travis-ci.org account (linked to github)
- appveyor.com account (linked to github)
- conan.io account
- digitalocean.com account

Part One - github
In the first part, we will assume that you are creating a personal home project, work on Open Source project or can store source files on some external resource, and ready to pay for it. What tasks you will be able to solve:
- understand how to automate assembling for Linux and Mac OS with Travis-CI
- understand how to automate assembling for Windows with the help of appveyor
- understand how to manage dependencies with the help of conan
- understand how to automate unit tests runs for all the platforms
- understand how automatically deploy with different configurations different compiler versions
- understand how to create your own packets for conan (first step towards CD)

Part Two - self hosted gitlab
During the second part we’l’ look at the situation when your working project has closed source code, and you don't want to have strong dependency for vendor lock infrastructure. What tasks you will be able to solve:
- how to deploy gitlab at digitalocean fast(DO)
- how to configure gitlab CI for your project


Conclusion

And we will build our own CI with conan and travis
Introduction
Developers’ mind has a common opinion, about their work which become completed after they’ve committed the code, and what happens next – not their problem. There is a great quote by Robert Highline for that thesis:
Each person should know how to change diapers, plan the invasion, harvest a pig, construct buildings, control a ship, write sonnets, make financial reports, build walls, set bones, assist dying, carry out an order, give out orders, cooperate, act alone, solve equations, analyze new problems, fertilize plants, program computers, cook tasty food, fight with dignity, die with dignity.

Specialization is the destiny of insects.

And instead of the opinion mentioned above, will put out our own thesis - the fact that code compilates on the developer’s environment and developer’s personal machine is not interesting for anyone! Our goal - Ii to make another step to the continuous integration, automate dependency resolution, assembling and unit testing for all the platforms which are interesting for us.

Continuous Integration
Continuous integration is the kind of practice, according to which, developers periodically (you can read it as daily) put out the results of the work into the main code branch. First use of that practice was introduced in the Buch method. Later, at extreme programming methodology, it improved with automatic unit tests run. Next step of current practice development is Continuous Delivery - the process where the distributive is created, after all acceptance tests are successfully completed, the distributive which ready to be published to the customer. And at the very end we can speak about Continuous Deployment during which all the changes that passed the testing phase successfully, automatically deployed to production. If you are already confused, you can imagine the following sequence:
1. Continuous integration
2. Continuous delivery
3. Continuous deployment
At the course of the current master-class we will speak about CI in the scope of C++ development.

Preliminary requirements
What is required from you:
- experience in using C++ (thanks, Cap!)
- laptop with any OS installed
- one of the compilers (Visual Studio >= 2015 / g++ >= 5.4 / clang++ >= 3.9 / Xcode >= 8.0)
- cmake >= 3.6 (you need to understand the syntax of CMakeLists.txt)
- git >= 2.10
- python >= 3.5
- pip3 >= 9.0
- github.com account
- travis-ci.org account (linked to github)
- appveyor.com account (linked to github)
- conan.io account
- digitalocean.com account

Part One - github
In the first part, we will assume that you are creating a personal home project, work on Open Source project or can store source files on some external resource, and ready to pay for it. What tasks you will be able to solve:
- understand how to automate assembling for Linux and Mac OS with Travis-CI
- understand how to automate assembling for Windows with the help of appveyor
- understand how to manage dependencies with the help of conan
- understand how to automate unit tests runs for all the platforms
- understand how automatically deploy with different configurations different compiler versions
- understand how to create your own packets for conan (first step towards CD)

Part Two - self hosted gitlab
During the second part we’l’ look at the situation when your working project has closed source code, and you don't want to have strong dependency for vendor lock infrastructure. What tasks you will be able to solve:
- how to deploy gitlab at digitalocean fast(DO)
- how to configure gitlab CI for your project


Conclusion

C++20 comes with some big new language features: modules, coroutines, concepts, spaceship, and many new libraries. But apart from all those, C++20 also offers many small language improvements, making C++ more powerful and expressive, but also safer and more consistent. This talk is an overview over all those smaller additions to the core language that will make your life easier. We will discuss much-needed improvements to existing facilities such as lambdas, CTAD, structured bindings, and initialisation, as well as brand-new language utilities that you may not yet have heard about!

In practice we frequently face the problems that are unreproducible on the developer side. Sometimes it's even impossible to request a remote access to the machine. In this talk we will review and give access on debugging typical tasks suck as core dumps, resource leakage, race conditions. We will use Windbg debugger and focus mostly on Windows platform.

Practical application development can lead to a task that appear to be general enough to extract an abstraction that is potentially useful for multiple applications. Bringing the solution to the level suitable for reusing (in contrast to an ad hoc solution for one particular application) can involve more efforts to extract variable details of the task and to express them in the pogramming language. The talk describes three abstractions related to one common topic, namely storing data in a buffer within a multithreaded application. The way from task analysis to implementation in C++17 is shown. These etudes serve as a good example for some features of modern C++.

Let's look at some metaprogramming tips and tricks while writing a state machine library

LLVM has a ton of optimizations and is suitable as a backend for many programming languages. It gets a little more complicated for managed languages and JIT scenarios. In this talk Egor will let us know about difficulties that they faced in C# while implementing LLVM backend

21 century is outside, non-productive implementation of C++ exception handling based on setjmp/longjmp is a past. Modern compilers such as gcc and clang use an advanced implementation of C++ exceptions called zero-cost exception handling. But is this real zero-cost? Yes, we pay by increasing the size of binary file and also in the case when the exception is thrown starting the stack unwinding process calling destructors for local objects, etc. But do we lose performance if an exception isn't thrown? Are there any restrictions on compiler optimizations? This talk describes how C++ exceptions affect compiler optimizations. Which optimizations can't be applied if the function can throw exceptions and which optimizations become more difficult to apply. Examples of exceptions implementations and compiler optimizations are considered based on LLVM. Talk aims to give an understanding of when it makes sense to build your application with -fno-exceptions and when you can enjoy C ++ exceptions, knowing that the code has not significantly lost performance compared to code where exceptions are disabled.

That talk will present the C++ world seen from Low Latency domain. The world where no dynamic allocations are welcomed, C++ exceptions are nearly not used, where STL containers are often not enough, and where developers often need to go deep down to assembly level to verify if the code really does its best.

The world has changed. Things that worked some time ago still do the job but become insufficient. Pair programming, code reviews, unit tests are still important and necessary but they cannot guarantee the sufficient level of quality and robustness of C++ projects. Many projects have grown a hundred times. The growth was happening steadily and not everyone understood what happened. Every big project consists of multiple layers and noone really understands how this stuff works. It's time for instruments and methodologies helping to save the quality and consistncy of code: DevSecOps, static analysis, dynamic analysis, platforms for measuring quality.

I want to speak about development of ORM library for SQLite3 in C++14 (https://github.com/fnc12/sqlite_orm). I want to share my experience in crearing ORM that may help to forget text queries and how this stuff gets adapted to C++ with the help of templates.

As a rule we can rely on the fact that compiler optimizes a binary file in way that a program works in the fastest way. But compiler doesn't know on what hardware the program will run. On top of that we would like compilation process to take a reasonable amount of time. This might lead to suboptimal results. I suggest to look at code examples for LLVM and see how to help the compiler to optimize the program and make result better or worse.

In C++ world there are a lot of tasks that require a big amount of boilerplat code: serialization, RPC, ORM, bindings for script languages. There are multiple approaches that simplify development of such kind of code, i.e. for serialization: write everything manually, put everything into macro, rely on Hana-based templates, combine one with another. But there's one approach that can replace all others: codegeneration. json, bson, xml, yaml, protobuf - there's a bunch of formats you can save your data in. Each format has its own library and not only one. Each library suggests their own way of data description and some of them even suggest a whole infrastructure which you have to adapt to and adapt your code to. This is not always convenient, you want freedom. You want your source code not to depend on a way serialization goes. Modern means of codegeneration may give you this freedom, you only need to know ho to apply them.

We will write a simple web-service from the client and server on C++. After that, the C++ part will end and set up the environment and infrastructure will start. We will provide a build determinability and tests run. Also, we will ease subsequent updating of dependent frameworks. Automate static checks, code verification, tests run. We will ensure the availability of the service, configure the infrastructure, balance the load and add automatic and manual scaling. And in the end, we will configure continuous delivery so that code will be in production 5 minutes after request, while even invalid changes and programmer errors will not affect his work.

That talk will present the C++ world seen from Low Latency domain. The world where no dynamic allocations are welcomed, C++ exceptions are nearly not used, where STL containers are often not enough, and where developers often need to go deep down to assembly level to verify if the code really does its best.