This landing page is currently under construction.
Please use the navigation links at the top.
These articles are aggregated from several news sources and
automatically filtered according to my interests (mostly PL stuff
with a little bit of algorithms and hardware thrown in). If they
seem haphazard, blame the weighting algorithm :-)
Just like programming trends and languages, programming books come and go. But these seven classics have stood the test of time. Some are newer than others, but all of them offer essential insight for new and experienced programmers:
A friend of mine approached me recently with a question: "What are your current thoughts on go-to platforms for building web apps? What would you choose for a web app? Ie. app that both should work as API, admin console, some end user facing stuff, etc".
Google maintains that Go’s simplicity is a selling point and it’s designed that way for maximising productivity in large teams but I’m not convinced. There are aspects of Go that are either seriously lacking or overly verbose because it doesn’t trust developers to get things right. This focus on simplicity was a concious decision made by the language designers and in order to fully understand why, we need to understand the motivation for developing Go and the state of mind of the creators.
Picat is a simple, and yet powerful, logic-based multi-paradigm programming language aimed for general-purpose applications. Picat is a rule-based language, in which predicates, functions, and actors are defined with pattern-matching rules. Picat incorporates many declarative language features for better productivity of software development, including explicit non-determinism, explicit unification, functions, list comprehensions, constraints, and tabling. Picat also provides imperative language constructs, such as assignments and loops, for programming everyday things. The Picat implementation, which is based on a well-designed virtual machine and incorporates a memory manager that garbage-collects and expands the stacks and data areas when needed, is efficient and scalable. Picat can be used for not only symbolic computations, which is a traditional application domain of declarative languages, but also for scripting and modeling tasks.