| module Warshall where | |
| import Data.Char ( isAlpha ) | |
| import Data.List ( nub, sort ) | |
| import System.Environment ( getArgs ) | |
| import Text.Parsec | |
| import Text.Parsec.String | |
| import Text.Printf ( printf ) | |
| type Vertex a = a |
| Value objects are an important concept in DDD. This kata is made both to learn value objects and to learn better ways of testing. | |
| Write a probability value object. It should contain the following methods: | |
| Probability CombinedWith(Probability) | |
| Probability InverseOf() | |
| Probability Either(Probability) | |
| if you forget your probability math: | |
| Either:P(A) + P(B) - P(A)P(B) | |
| CombinedWith: P(A)P(B) |
| Greg's Stop Loss Kata | |
| Testing is very hard when time is involved ... | |
| A trailing stop loss is a term used in financial trading. For a very in depth explanation you can read here http://www.investopedia.com/articles/trading/03/080603.asp and http://en.wikipedia.org/wiki/Order_(exchange)#Stop_orders | |
| However we do not need a huge amount of background in order to do the kata as we are going to limit the problem a bit. | |
| The general idea is that when you buy into a stock at a price say $10. You want it to automatically get sold if the stock goes below $9 (-$1). If we use the term "trailing" that means that id the price goes up to $11 then the sell point becomes $10. |
##How Homakov hacked GitHub and the line of code that could have prevented it
Please note: THIS ARTICLE IS NOT WRITTEN BY THE GITHUB TEAM or in any way associated with them. It's simply hosted as a Gist because the markdown formatting is excellent and far clearer than anything I could manage on my personal Tumblr at peternixey.com.
If you'd like to follow me on twitter my handle is @peternixey
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
If you're coming to the Property-Based TDD As If You Meant It Workshop, you will need to bring a laptop with your favourite programming environment, a property-based testing library and, depending on the language, a test framework to run the property-based-tests.
Any other languages or suggestions? Comment below.
.NET (C#, F#, VB)
Python:
| import spark.streaming.StreamingContext._ | |
| import spark.streaming.{Seconds, StreamingContext} | |
| import spark.SparkContext._ | |
| import spark.storage.StorageLevel | |
| import spark.streaming.examples.twitter.TwitterInputDStream | |
| import com.twitter.algebird.HyperLogLog._ | |
| import com.twitter.algebird._ | |
| /** | |
| * Example of using HyperLogLog monoid from Twitter's Algebird together with Spark Streaming's |
If you have two days to learn the very basics of modelling, Domain-Driven Design, CQRS and Event Sourcing, here's what you should do:
In the evenings read the [Domain-Driven Design Quickly Minibook]{http://www.infoq.com/minibooks/domain-driven-design-quickly}. During the day watch following great videos (in this order):
| // Just before switching jobs: | |
| // Add one of these. | |
| // Preferably into the same commit where you do a large merge. | |
| // | |
| // This started as a tweet with a joke of "C++ pro-tip: #define private public", | |
| // and then it quickly escalated into more and more evil suggestions. | |
| // I've tried to capture interesting suggestions here. | |
| // | |
| // Contributors: @r2d2rigo, @joeldevahl, @msinilo, @_Humus_, | |
| // @YuriyODonnell, @rygorous, @cmuratori, @mike_acton, @grumpygiant, |
