Not all projects are on ideal paths II (Tim Finnerty)

This is another story of a project, that did not go as well as it could have gone while I was there. From unsuccessful projects we can learn a lot, so there will be stories like this once in a while. The first one was about Tom Rocket.

Tim Finnerty

It was the time, when all the cool companies tried to introduce Java. And some of the new Java projects failed, causing the companies to go back to C, which again scared other companies from doing this step. But some companies did not get scared by this. They embraced the new Java-fashion at a time when it still was not clear whether or not this was a good idea. What could possibly go wrong?

Well, in those days the experienced guys did not want to move to Java. It was slow, it was unreliable, not mature,… Maybe for Applets, maybe more generally for GUIs to get rid of VisualBasic, but Java on the server was considered a bad joke. For the server real people used real C, of course on Unix or maybe Linux, which was not really such a bad idea in those days. But there were the young people. Or the ones who had stayed young. They often just had finished their education and firmly believed that by just using technology „xyz“ everything would become great. xyz can be a development method (spiral model in those days, agile today), an architecture (microservices), a paragdigm („OO“, „functional“), a framework („enterprise edition“), a tool or a programming language (yeah, Java).. Often this first enthusiasm ends in a disaster: The money has been spent, the developers are leaving and the software is further away from being useful than anybody would like to admit. In lucky cases there is still some money left to do it right. Maybe even to do it right in Java.

That is were we are coming in. I do not really know the earlier history, but according to the management it was a total disaster. Now Tim Finnerty (real name known to the author) was the new technical lead, team architect or whatever this role is called. He embraced the new technology, but promised to not overstrech it. A bit of old school. Sounds good, because it is exactly what managers want to hear. No more risky experiements, but this time it needs to become a success.

So Tim Finnerty defined, how we had to work. He knew Java, he knew databases and especially Oracle, he knew the web, he even knew Perl. And he knew OO. Better than anybody else, so we did the real thing. Great head start. And everybody had to program according to Tim’s rules.

Of course we were using Java enterprise edition. That meant, that we were programming against some Weblogic application server, that was hard to install, hard to run, required a few minutes of startup time for each minor change of the software that we were writing and forced to a very archaic and primitive programming model. But that was cool and it was the future, which unfortunately proved to be true. Even though it has at least become usable by now. So far nothing to blame on Tim, because it is kind of the stack that everybody used.

Now to the OO and the database. Each database table represented a „Business Object“, with a name like XyzBO. So most of the time, we wrote a class XyzBO plus a few more to fulfill the greed and need for boilerplate code of the old J2EE-world. XyzBO was a enterprise java bean. A stateless session bean, to be accurate. Which meant, that we wrote methods of this EJB, which were basically procedures of the pre-OO-world. But within we could of course use the whole OO-toolset. Which we did. So the class to represent any data from the database was actually called Data. It was a minor subset of the standard Perl data structures, which meant that Data was a list of hash maps, which could behave just like a hash map if it had only one entry. Database queries returned Data, or of course null, if nothing was found. Nobody would ever want to use an empty collection. Pretty much the opposite of what we are now doing the hard way by introducing Optional or Option to avoid the null. But it was easy to just write
if (data == null) { data = new Data(); }
at least for the ones who new this trick.
So data resembled the content of the database or of the query result, with the column names as keys and the values as objects. When working with these, it was really easy. Just know the attribute name accurately. Get the value from data. See if it is null. If not, cast it to the real type, and voila….

The database was designed according to Tim’s advice, he had to review every table. It was mandatory to have as unique key and as first column a string of around 700 characters, which was called HANDLE. Each table had a business primary key, which was always consisting of several columns. Because the system allowed multiple instances of the software to run on the same database, there was always one column called „SITE“ in this logical primary key. But there were no primary keys defined in the database. The unique HANDLE was enough. It contained the name of the BO, like XyzBO, followed by a colon and followed by the concatenation of all the logical primary keys, separated with commas. The date had to be converted to a string using a local US format, not ISO, of course. All foreign keys were defined using HANDLE. In the end more than half of the DB space was wasted for this stupidity. But each single handle value started with an XyzBO:, to remind us that we were programming OO.

And now booleans. It was forbidden to use the boolean type of Java. All booleans were strings containing the words „true“ and „false“. This went like that all the way to the web interface.

At that time web frameworks did not yet exist or were at least unknown. So the way to go was to write JSPs, which contained kind of dynamic web pages and to write servlets to control the flow and access the EJBs. Now according to Tim it was too hard to learn servlets as well, so it was forbidden to use them and instead a connection-JSP had to be written, which did not display anything, but only contained a <% in the beginning and a %> in the end and the code between.

A lot of small and larger stupidities, that were forced on the team. Most people were new to Java and to OO and did not even realize that there was anything wrong, apart from the fact, that it was kind of hard to get stuff done. Some stupidities were due to the fact that the early J2EE really sucked, but mostly it was Tim, who forced everyone to his level. This story happened a long time ago. Tim has already retired. I would say he is one of the guys, who retire as a Junior.

There is (almost) nothing wrong with stupidity. And there is (almost) nothing with arrogance. But the combination really sucks. Especially if it it taken serious by the manager or has to be taken serious by the team.

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LongDecimal

Disclaimer: This article is an occasion, where you might need some of the presumably useless mathematics that you might have learned in school and university. If this bothers you, maybe you should wait for the next article in about two weeks time.

LongDecimal is a library that I have provided for Ruby. It is available as a ruby gem. It was originally intended to provide something like BigDecimal for Java. There is a BigDecimal, but it is not really the same. For writing finance applications, such a class is useful, so I wrote one that covers what Java’s BigDecimal has. It ended up by having a lot more, but we will get to that later.

So the general idea is that we do math with a subset of the rational numbers (\mathbb{Q}) \mathbb{D} = \{ \frac{x}{10^n} : x \in \mathbb{Z} \wedge n \in \mathbb{N}_0\}. This is not quite the truth, because the n actually carries information that we care about, so we would actually define

    \[\mathbb{D} = \{ (\frac{x}{10^n}, n) : x \in \mathbb{Z} \wedge n \in \mathbb{N}_0\}.\]

So we actually want to allow the numerator x to be a multiple of 10 and we use this to express the precision as to how many digits after the decimal point are explicitely part of our number. Having more decimal places after the decimal point expresses more precision.

Now we try to use mathematical operations +, - and \cdot on \mathbb{D}. It turns out that we have three different cases. The ring operations can be defined without problems, even though \mathbb{D} is not quite a ring, as we will see. But it is good enough for most purposes.

  • (\frac{x}{10^n}, n) + (\frac{y}{10^m}, m) = (\frac{x}{10^n} + \frac{y}{10^m}, \max(n, m))
  • (\frac{x}{10^n}, n) - (\frac{y}{10^m}, m) = (\frac{x}{10^n} - \frac{y}{10^m}, \max(n, m))
  • (\frac{x}{10^n}, n) \cdot (\frac{y}{10^m}, m) = (\frac{xy}{10^{n+m}}, m+n)

Addition and Subtraction actually lose information if n\ne m, because we might have an input with lower precision and in the end pretend to have a result of the higher precision. But not losing numerical information is considered more important and implicit rounding should be avoided at all costs, at least for the basic operations.

\mathbb{D} is not a ring, but it is a Semiring. The zero is not universally unique, but we seem to have many zeros (0, n). This is not the problem, because only (0, 0) would act as an additive neutral element. What we lack are additive inverse elements. If we have an element (x, n) with n>0, there is no element (y, m), such that (x,n)+(y,m)=(x+y, \max(n,m) = (0, 0). The distributivity, required for a semiring, can be seen easily:

  • ((\frac{x}{10^n}, n) + (\frac{y}{10^m}, m))\cdot (\frac{z}{10^l}, l) = ((\frac{x}{10^n}+\frac{y}{10^m})\cdot\frac{z}{10^l}, l+\max(m,n)
  • (\frac{x}{10^n}, n)\cdot (\frac{z}{10^l}, l) + (\frac{y}{10^m}, m)\cdot (\frac{z}{10^l}, l) = (\frac{x}{10^n}\cdot\frac{z}{10^l}+\frac{y}{10^m}\cdot\frac{z}{10^l}, \max(l+m,l+n)

But since we do computer programming and not math and only use math as a tool to help us, it is kind of OK, that it is only a semiring and not a ring, as long as we know it.

Division is a special case, because it is not always possible to express the exact numerical value of the quotient in \mathbb{D}, for example 3.0/7.0 = \frac{3}{7}, where the denominator is not a power of ten. To do such operations, a rule on how to round needs to be provided. This is cumbersome, because it blows up our formulas, so we define a set \mathbb{E}=\{(r, n) : r \in\mathbb{Q} \wedge n \in\mathbb{N}_0\}. Now the quotient of two elements of \mathbb{D} is a member of \mathbb{E}. And we have the rules

  • (\frac{x}{10^n}, n) / (\frac{y}{10^m}, m) = (\frac{x}{10^n} / \frac{y}{10^m}, p(n, m))
  • (r, n) + (s, m) = (r+s, \max(n, m))
  • (r, n) - (s, m) = (r-s, \max(n, m))
  • (r, n) \cdot (s, m) = (rs, n+m)
  • (r, n) / (s, m) = (\frac{r}{s}, q(n,m))

where p and q somehow try to estimate how precise the result of the division might be. The basic idea is to do the whole calculation that includes the division and round the result to the desired number of decimal places after the point and with the rounding mode desired.

Now the power is a hard one. Arbitrary powers can of course be defined and are supported, but most of the time, the exponent is actually an integer. These cases can be defined nicely. For exponents m\ge 0 we actually get a result in \mathbb{D} and for negative exponents m < 0 we get results in \mathbb{E}:

  • \bigwedge_{n\ge 0}:(\frac{x}{10^n}, n) ^m = \frac{x^m}{10^{mn}}, mn)
  • \bigwedge_{n < 0}:(\frac{x}{10^n}, n) ^m = \frac{x^m}{10^{mn}}, mn)

For non-integral exponents, the calculation of powers falls back to Ruby’s built in power and transforms elements of {\mathbb{D} and \mathbb{E} involved into rational numbers. These are of limited use, but they are provided and work and can be used, when needed. There is a more general power function, that has additional parameters for the desired rounding and number of digits after the decimal point. While this library goes long ways to achieve decent accuracy and speed, there are certainly possible input parameters that will result in extremely long calculation times or results that are much less accurate than claimed. Such examples are „hard“ to find and should not harm the practical usefulness of the library too much. Similar libraries in the Java world like BigDecimal do not even try to calculate powers with arbitrary exponents and the Ruby builtin library BigDecimal (which is something slightly different) does have its issues when calculating arbitrary powers.

Rounding functions are there to convert a numerical type that is at least viewable as a subset of \mathbb{R} to \mathbb{D}. The actual rounding has to be implemented, but it has been done for \mathbb{D}, \mathbb{E} and the built in types of Ruby except for Complex (\mathbb{C}). For complex numbers, the real and the imaginary part are rounded and stuffed into a new complex number.

Rounding needs two pieces of information, the desired precision (number of decimal places after the decimal point) and the rounding mode. There are different methods for rounding, but they all follow the same basic rules. A special case is the round_to_allowed_remainders, which does a residue class rounding.

There are many rounding modes. Rounding can be towards 0, away from 0, towards infinity or towards negative infinity. This boils down to cutting off all digits but n (or adding zeros) and possibly adjusting the result by one, if the cut off part contained anything but zeros. Other rounding modes take a mean between the two adjacent result candidates and decide by that which one to take, requiring an extra rule for the case that the value that needs to be rounded happens to be exactly on the border.

Generalized powers and all functions that return something irrational like square roots, cubic roots, exponential functions, logarithms and in the future also trigonometric functions needs to be calculated with the number of digits required and a rounding mode. Currently square roots (sqrt) and cube roots (cbrt) are calculated accurately according to these rounding parameters. For the transcendential functions (logarithms, exponential functions, power, trigonometric functions) minor deviations from the mathematically accurate result are still possible. Since the major usage of the library is expected to deal with the basic operations only, this is considered acceptable. To really work with the transcendental functions, using interval arithmetic in conjunction with long decimal would anyway be a better way, so the necessary guarantee to be given would be to provide a result that is close, but guaranteed to be lower or equal than the real mathematical result and one that is guaranteed to be greater or equal. Progress in this area is not going to happen very soon, unless someone would be volunteering to help with this or someone would be volunteering to sponsor the development.

Also it might be interesting to port this library to other languages, even to Java, because it has become much more sophisticated than Java’s BigDecimal library. Again this is unlikely to happen too soon without any help.

The current priority is to keep this library working with recent Ruby versions and to add the missing trigonometric functions.

Use it as follows:
gem install long-decimal
to install it. Then use it in your code with:
require "long-decimal"

A remark for people who are mathematically inclined: The definition of the natural numbers \mathbb{N} is not totally universal. Sometimes we have \mathbb{N} = \{0, 1, 2, 3, 4,\ldots\} and sometimes we have \mathbb{N} = \{1, 2, 3, 4,\ldots\}. To avoid this, I am using \mathbb{N}_0 = \{0, 1, 2, 3, 4,\ldots\}, even though the index _0 is kind of ugly. I agree with Dijkstra that we should prefer to include the 0 in the natural numbers.
Another remark for mathematically interested readers: If we were defining \mathbb{D}=\{ \frac{x}{10^n} : x \in \mathbb{Z} \wedge n \in \mathbb{N}_0\}, we would actually have a ring. If we now replaced 10 with a prime number p, we would approach the realm of p-adic numbers (\mathbb{Q}_p). This is well worth supporting by a library as well, but it is quite a different story and of course only of interest to a small group who actually knows p-adic numbers and works with them.

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TruffleRuby

The language Ruby is one of the most beautiful languages. A lot of things can be done, it has a good level of abstraction, it has chosen some very good defaults, has provided some great ideas that I have not discovered in any other language that I know well and provides a lot of flexibility. But I could no longer recommend it for projects that might require a good performance. I won’t go into the issue of static typing vs. dynamic here. Ruby is following the dynamic typing path and if you think that is a bad idea at all, then it will never become your favorite. But this is an issue with pros and cons. The big disadvantage of Ruby is that it is not very good in terms of performance. The single threaded performance is somewhat better in many reasonable languages like Java, Python, Scala, Clojure, C, C#, F# and some others .. And it gets worse when we want to use multiple cores, because Ruby does not run them simultaneously, but uses a global lock which ensures that only one thread at a time is running. Or in case of JRuby just crashes or yields wrong results in certain mulithreaded programs that we could write.

One approach is to go for immutability as a default, which allows quite painless multithreading. Scala and Clojure follow this route, for example. It is hard to write good code with this constraint or to make good use of very local mutability without leaking it outside, but under these conditions multiple threads are just working fine without deadlocks, crashes or falsified results. Another approach is to just copy structures and leave its own copy to each thread. There are ways to do a lot on this path, but the copying costs a lot of memory and performance and it is not always a gain.

Now Ruby heavily relies on mutable structures for strings and collections. It is not reasonable to go for a total paradigm change in this aspect. But there are some ways to get good and safe and fast operations on these collections and strings without breaking this. One idea is to work with chunks of collections or strings. For strings, the string that we are working with is described as a concatenation of such strings. Many operations can be made by just concatenating multiple strings together and possibly replacing one of them with a copy that can be made as needed. This is called Rope. A similar approach can be applied to collections. Then a smart locking mechanism is applied to the shorter string or collections when needed, but many operations can avoid locking or block much less of the structure.

Also the compiler can analyze the program and simplify it to a great extent, compile it to the JVM, which in conjunction with hot spot optimizations will make it run really fast. Now this TruffleRuby is much faster than other Rubies, by a factor of about 10. It uses GraalVM and it actually supports a lot of C-extensions for libraries through the feature of GraalVM that they can be eventually compiled to the JVM. It does not work if extensions rely on implementation details of the Ruby structures in C and it often does not work for C-extensions that go to low level OS functionality. The current version of TruffleRuby is not really ready to use in conjunction with Ruby on Rails, which is kind of a no go, because Ruby is usually used in conjunction with Rails. My impression is that it will be possible to use it with Rails in a year or two.

Hearing of this in a talk by Benoit Daloze in the local Rails user group in Zürich was a great and positive surprise. Ruby gets interesting again.

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How to draw lines, circles and other curves

These ideas were developed more than 30 years without knowing that they were already known at that time…

Today the graphics cards can easily do things like this in very little time. And today’s CPUs are of course really good at multiplying. So this has lost a lot of its immediate relevance, but it is a fun topic and why not have some fun…

Let us assume we have a two dimensional coordinate system and a visible area that goes from x_{\min} to x_{\max} and y_{\min} to y_{\max}. Coordinates are discrete.

In this world we can easily measure an angle against a (directed) line parallel to the x-axis, for example up to an accuracy of 45^\circ=\frac{\pi}{4}:

  • y=0 \wedge x > 0 \implies \alpha = 0 (= 0^\circ)
  • 0 < y < x \implies 0 < \alpha < \frac{\pi}{4}(=45^\circ)
  • 0 < y = x \implies \alpha = \frac{\pi}{4}
  • 0 < x < y \implies \frac{\pi}{4} < \alpha < \frac{\pi}{2}(=90^\circ)
  • x = 0 \land y > 0\implies \alpha = \frac{\pi}{2}
  • x < 0 \land y > 0 \land |x| < |y|\implies \frac{\pi}{2} < \alpha < \frac{3\pi}{4}(=135^\circ)
  • x < 0 \land y > 0 \land -x = y\implies \alpha = \frac{3\pi}{4}(=135^\circ)

So let us assume we have a curve that is described by a polynomial function in two variables x and y, like this:

    \[f(x, y) = \sum_{j=0}^m\sum_{k=0}^n a_{j,k}x^jy^k = 0\]

We have to apply some math to understand that the curve behaves nicely in the sense that it does not behave to chaotic in scales that are below our accuracy, that it is connected etc. We might possibly scale and move it a bit by substituting something like c_1u+c_2 for x and c_3v+c_4 for y.

For example we may think of

  • line: f(x,y)=ax+by+c
  • circle: f(x, y)=x^2+y^2-r^2
  • eclipse: f(x, y)=\frac{x^2}{a^2}+\frac{y^2}{b^2}-1

We can assume our drawing is done with something like a king of chess. We need to find a starting point that is accurately on the curve or at least as accurately as possible. You could use knights or other chess figures or even fictive chess figures..

Now we have a starting point (x_0, y_0) which lies ideally exactly on the curve. We have a deviation from the curve, which is f(x_0, y_0)=d_0. So we have f(x_n, y_n)=d_n. Than we move to x_{n+1}=x_n + s and y_{n+1}=y_n+t with s, t = \{-1, 0, 1\}. Often only two or three combinations of (s, t) need to be considered. When calculating d_{n+1} from d_n for the different variants, it shows that for calculating d_{n+1}-d_n the difference becomes a polynomial with lower degree, because the highest terms cancel out. So drawing a line between two points or a circle with a given radius around a given point or an ellipse or a parabola or a hyperbola can be drawn without any multiplications… And powers of n-th powers of x can always be calculated with additions and subtractions only from the previous x-values, by using successive differences:
d_{m,1}=(x-m)^n-(x-m-1)^n
d_{m,l+1}=d_{m+1,l}-d_{m,l}
These become constant for l=n, just as the lth derivatives, so by using this triangle, successive powers can be calculated with some preparational work using just additions.
It was quite natural to program these in assembly language, even in 8-bit assembly languages that are primitive by today’s standards. And it was possible to draw such figures reasonably fast with only one MHz (yes, not GHz).

We don’t need this stuff any more. Usually the graphics card is much better than anything we can with reasonable effort program. Usually the performance is sufficient when we just program in high level languages and use standard libraries.

But occasionally situations occur where we need to think about how to get the performance we need:
Make it work,
make it right,
make it fast,
but don’t stop after the first of those.

It is important that we choose our steps wisely and use adequate methods to solve our problem. Please understand this article as a fun issue about how we could write software some decades ago, but also as an inspiration to actually look into bits and bytes when it is really helping to get the necessary performance without defeating the maintainability of the software.

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2019 — Happy New Year

Gott nytt år! — Godt nytt år! — Felice anno nuovo! — Καλή Χρονια! — Щасливого нового року! — Срећна нова година! — С новым годом! — Feliĉan novan jaron! — Bonne année! — FELIX SIT ANNUS NOVUS — Gullukkig niuw jaar! — Un an nou fericit! — Frohes neues Jahr! — Happy new year! — ¡Feliz año nuevo! — Onnellista uutta vuotta! — عام سعيد

This was created by a Java-program:

import java.util.Random;
import java.util.List;
import java.util.Arrays;
import java.util.Collections;

public class HappyNewYear {

    public static void main(String[] args) {
        List list = Arrays.asList("Frohes neues Jahr!",
                                          "Happy new year!",
                                          "Gott nytt år!", 
                                          "¡Feliz año nuevo!",
                                          "Bonne année!", 
                                          "FELIX SIT ANNUS NOVUS", 
                                          "С новым годом!",
                                          "عام سعيد",
                                          "Felice anno nuovo!",
                                          "Godt nytt år!", 
                                          "Gullukkig niuw jaar!", 
                                          "Feliĉan novan jaron!",
                                          "Onnellista uutta vuotta!",
                                          "Срећна нова година!",
                                          "Un an nou fericit!",
                                          "Щасливого нового року!", 
                                          "Καλή Χρονια!");
        Collections.shuffle(list);
        System.out.println(String.join(" — ", list));
    }
}

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Christmas 2018


Feliĉan Kristnaskon! — Frohe Weihnachten! — God Jul! — Merry Christmas! — Joyeux Noël! — クリスマスおめでとう ; メリークリスマス — Срећан Божић! — Buon Natale! — Hyvää Joulua! — З Рiздвом Христовим! — ميلاد مجيد — С Рождеством! — Crăciun fericit! — ¡Feliz Navidad! — καλά Χριστούγεννα! — Natale hilare! — God Jul! — Prettige Kerstdagen!

As I said, I am learning some Python, so let’s use it. I created the message above with this program:

#!/usr/bin/python3
import random
arr = [
    "Frohe Weihnachten!",
    "Merry Christmas!",
    "God Jul!",
    "¡Feliz Navidad!",
    "Joyeux Noël!",
    "Natale hilare!",
    "С Рождеством!",
    "ميلاد مجيد",
    "Buon Natale!",
    "God Jul!",
    "Prettige Kerstdagen!",
    "Feliĉan Kristnaskon!",
    "Hyvää Joulua!",
    "クリスマスおめでとう ; メリークリスマス",
    "Срећан Божић!",
    "Crăciun fericit!",
    "З Рiздвом Христовим!",
    "καλά Χριστούγεννα!"
]
random.shuffle(arr)
print(" — ".join(arr))
print("\n")

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Indexing of Arrays and Lists

We index arrays with integers. Lists also, at least the ones that allow random access. And sizes of collections are also integers.
This allows for 2^{31}-1=2147483647 entries in Java and typical JVM languages, because integers are actually considered to be 32bit. Actually we could think of one more entry, using indices 0..2147483647, but then we would not be able to express the size in an signed integer. This stuff is quite deeply built into the language, so it is not so easy to break out of this. And 2’000’000’000 entries are a lot and take a lot of time to process. At least it was a lot in the first few years of Java. There should have been an unsigned variant of integers, which would in this case allow for 4’000’000’000 entries, when indexing by an uint32, but that would not really solve this problem. C uses 64 bit integers for indexing of arrays on 64 bit systems.

It turns out that we would like to be able to index arrays using long instead of int. Now changing the java arrays in a way that they could be indexed by long instead of int would break a lot of compatibility. I think this is impossible, because Java claims to retain very good backward compatibility and this reliability of both the language and the JVM has been a major advantage. Now a second type of arrays, indexed by long, could be added. This would imply even more complexity for APIs like reflection, that have to deal with all cases for parameters, where it already hurts that the primitives are no objects and arrays are such half-objects. So it will be interesting, what we can find in this area in the future.

For practical use it is a bit easier. We can already be quite happy with a second set of collections, let them be called BigCollections, that have sizes that can only be expressed with long and that are indexed in cases where applicable with longs. Now it is not too hard to program a BigList by internally using an array of arrays or an array of arrays of arrays and doing some arithmetic to calculate the internal indices from the long (int64) index given in the API. Actually we can buy some performance gain when resizing happens, because this structure, if well done, allows for more efficient resizing. Based on this all kinds of big collections could be built.

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Clojure Exchange 2018

I visited Clojure Exchange 2018 in London.
Since there was only one track and I attended all talks, it is easy to just refer to the schedule.

Interesting topics, that came up multiple times in different flavors where immutability, stories of building real life applications, music, java and clojure and the transition, clojure script, emacs and cider…

I did a lightning talk myself about Some Thoughts about Immutability and its Limits.

Links

  • Clojure
  • Clojure Exchange 2018
  • Clojure Exchange 2016
  • Clojure
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Devoxx Kiew 2018

In the end of 2018 the number of conferences is kind of high. A great highlight is the Devoxx BE in Antwerp. But it has now five partner conferences in London, Paris, Krakow, Morocco and Kiev. So I decided to have a look at the one in Kiev.

How was it in comparison to the one in Belgium? What was better in Kiev: The food was way better, the drinks in the first evening (Whisky and Long Drinks vs. Belgium Beer) might be considered better, there were more people engaged to help the organizers…
What was better in Belgium: There were still a bit more speeches. While the location in Kiev was really great, in Belgium the rooms were way better for the purpose of providing a projection visible for everybody and doing a video recording that did not disturb the audience.
The quality of the speeches was mostly great in both locations. In Kiev they gamified the event a bit more..

Generally there was a wide range of topics and the talks were sorted into the following thematic groups:

  • Methodology & Culture
  • JVM Languages
  • Server Side
  • Architecture & Security
  • Mobile & IoT
  • Machine Learning & AI
  • Big Data & Data Mining
  • Cloud, Containers & Infrastructure
  • Modern Web & UX

See the schedule for the distribution…

I attended on Friday:

I attended on Saturday:

A lot to learn.

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Devoxx Antwerp 2018

In 2018 I am visiting a few conferences. A great highlight is the Devoxx BE in Antwerp, which I had the privilege of visiting 2012, 2013, 2014, 2015, 2016 and 2017.

As it should be, it is not just the same every year, but content and speakers change a bit from year to year.

Some topics that got a lot of attention were functional programming, artificial intelligence, Big Data, Machine Learning, clouds, JVMs, Kotlin

There was less about other JVM languages (apart from Kotlin), so Scala, Clojure, Groovy or Ceylon were covered little or not at all and Android used to be more present in other years. I would say that Ceylon has become irrelevant, probably because Kotlin was too similar and came out the same time and won. Groovy has its niche, Clojure has its niche, Scala and Kotlin have become mature and are now the two mainstream alternatives to Java, but themselves much smaller than Java. This was represented in the conference, taking into account that Scala has its own large conferences, like Scala Days, Scala Exchange, Scala World and a lot more.

Some side issues that might worry some of us did come up occasionally. Was it bad, that IBM bought Red Hat? At least they paid around 34’000’000’000 USD, which is more than 2’500’000 USD per employee. There are probably no other assets in terms of buildings, patents, hardware or whatever, that would justify this price, so IBM probably will have an interest to keep a large number of these employees and not scare them away by too much „IBM-culture“. We will see, but no reason to get immediately worried. Oracle wants money for running their JVM in production after more than 6 months. This can be avoided by always switching to the newest version or by relying on the JDKs offered by alternative sources like Amazon, RedHat…

Microsoft was a sponsor and had a booth. Their topic was not MS-Windows and MS-Office and MS-SQL-Server, but Azure, which can be used with Linux and Java and PostgreSQL, for example. The company did change a bit since the days of Steve Ballmer and we will see if this is an excursion or a continuous direction.

And James Gosling was there at the opening, as a surprise.

Generally there was a wide range of topics and the talks were sorted into the following thematic groups:

  • Methodology & Culture
  • Java Language
  • Programming languages
  • Architecture & Security
  • Big Data & Machine Learning
  • Mind the Geek
  • Server Side Java
  • Modern Web & UX
  • Cloud, Containers & Infrastructure
  • Mobile & IoT

See the schedule for the distribution…

I attended on Wednesday:

I attended on Thursday:

I attended on Friday:

It was a great conference. A lot of new ideas.

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