Jacek's Blog
Software Engineering Consultant
This article is about the C++17 STL Cookbook, which got published this week. After about 6 months of writing, I am happy that it is out the door and hope it helps and inspires its readers to write modern C++ code.
Sometimes, casting is just inevitable. And then there’s even not much science behind it, at least it seems so. Once some address is provided in a variable of the right size, a typed pointer can be casted out of it, and then the object can be accessed via its members and methods as usual. In some situations it is really easy to get the casting wrong, leading to interesting bugs. This article describes an example situation and a proper fix.
The C++ STL comes with stream style character output, which is an alternative to the classic printf like format function collection of the C library.
For different reasons, some C++ programmers still stick to printf like formatting.
This article demonstrates the pprintpp (open source, and available on Github) library, which tries to make printf use comfortable and safe while avoiding any runtime overhead.
There are a lot of algorithms which can be implemented using recursive or iterative style.
Actually, everything can be implemented in both styles.
For a lot of algorithms, the recursive version is simpler to read, write, and understand.
But nevertheless, programmers know, that recursive functions burden a lot of memory consumption, because there is usually a call instruction per recursive call, which puts another call frame on the stack.
Interestingly, this is not true for some special cases.
Sometimes there is the requirement to generate a range of numbers from some algorithm. Be it a simple range of increasing numbers, or only odd numbers, or only primes, or whatever. Some calculations can be optimized by memorizing some values for the calculation of the next number, just as this applies for fibonacci numbers. This article shows how to wrap such calculations into iterators in order to have performant, and nicely encapsulated algorithms.
Soon, after writing my first meta programs with C++ templates, i realized, that certain programming patterns lead to sky rocketing compile times. I came up with rules of thumb like “Prefer pattern matching over if_else_t”, and “Prefer nested type lists over variadic type lists”. But i did not know how much faster which pattern is, i just knew about tendencies. Finally, i sat down to write some compile time benchmarks, and this blog posts presents the results.
In some situations, it can be useful ot generate sequences of numbers at compile time. This article shows how to generate integer sequences with C++ templates, and gives an example how to use it.
This article completes a series which aims at explaining how to implement a Brainfuck Interpreter as a template meta-program which runs at compile time.
Turing Machines consist of a tape with memory cells, a tape reader like cassette drives and a program table. Implementing the tape drive part with an array and a pointer is a trivial thing to do with imperative programming languages. It becomes more interesting when learning purely functional programming, especially in the context of template meta programming in C++. As a preparation for the next article, i will show how to implement a turing tape based on type lists, usable at compile time.
Type lists are an important way to represent ordered and unordered sets of types at compile time. These types can be real structure- or class types bundling runtime algorithms etc., but they can also convey actual data at compile time. In order to apply certain compile time processing to data, this data needs to be transformed from and to other representations, which can be provided by the programmer and consumed by run time programs. This article shows how to transform back and forth between strings and character type lists.