CryptoMate – an Amazon Alexa Skill for live price cryptocurrency info

Having jumped on the crypto currency bandwagon a couple of months ago, I have just released a nifty Amazon Alexa app CryptoMate that gives you live price information for over 400+ crypto currencies, including favourites such as bitcoin, ethereum, dash, litecoin, ripple, monero, zcash, antshares, stratis, waves and many more.

Just enable the CryptoMate skill on your Echo device and say:

“Alexa, ask crypto mate how much is bitcoin”

or simply

“Alexa, ask crypto mate ethereum”

Alexa will then hopefully reply with something like:

“The current price of bitcoin is 2345.24 dollars”.

Future updates will provide information about market cap, percentage change, conversion into other fiat currencies and much more.

All the price information is pulled from REST API where prices update every 5 minutes. Code is fully open source and can be found on my GitHub repo.

For the full list of supported currencies head over here.

DOWNLOAD the skill from the Amazon Alexa Skill store for free!

You can donate BTC to support this product here: 172Pm6dC9jhEfPxEpnUpcPL7EadSPWYW9U

Model-Driven Engineering (MDE) in a nutshell

Models have been an integral part of software engineering and have always been used to support different stages of the software development lifecycle of a product. Model-driven engineering (MDE) is a modern approach to software engineering, which obeys the core principle that “Everything is a model” and focuses on the creation, manipulation and management of conceptual models of software systems. Models provide an abstract representation of the system and above all, allow for managing complexity by describing application-specific solutions using high-level graphical modelling, rather than a programming language. Thus, abstraction from the implementation details allows for an evaluation of the target system properties very early in the design, as it is less expensive to modify or refine models of the system at a high-level prior to development, than after it has been fully built.

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The Artificial Bee Colony (ABC) algorithm as a non-standard computational method

Swarm intelligence is defined in the academic literature as the ability to design algorithms inspired by the collective behaviour of decentralized and self-organized social insect colonies. A well-known example of swarm intelligence is a honey bee swarm which has enthused researchers to develop algorithms based on the various activities taking place within a bee colony. An example of one such algorithm is the Artificial Bee Colony (ABC) algorithm proposed by Karaboga in 2005 which simulates the foraging behavior of bees for solving optimization problems and is the one of the most widely studied swarm based algorithms so far.

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A Review of Static and Dynamic Scoping in Programming Languages

All programming languages allow names to be associated with values by means of definitions, and a name is said to be in the scope of its definition. When a name is mentioned in a program, its definition (if any) must be known, in order for its invocation to make sense. However, most languages allow names to be re-defined in a program – the rules for determining to which definition a name refers, are called the scoping rules.
There are two principal scoping methods: static and dynamic. This post will firstly explain these two concepts, comparing their similarities and differences. The uses of the two methods will be discussed, illustrating these with code from actual programming languages. Finally the essay will conclude with a critical summary of the pros and cons of static and dynamic scoping for present day programming problems.

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