Why I love Hebrew

After the last post I feel obliged to say a few words about Hebrew as well. And as it will probably turn out, there will be more than a few by the time I finish writing this.

Japanese is like art. You look at it, you’re fascinated with it, and you may see as many meanings in it as your imagination will allow you. Hebrew, on the other hand, is like science.

In many ways, Hebrew is very similar to Western languages. It has a proper alphabet (no vowel letters or capital ones, though), it has spaces (unlike Japanese), it has grammar and spelling rules and all that stuff. What makes it special (along with Arabic, probably) is the structure of a typical Hebrew word, I mean mostly nouns, adjectives and verbs here.

A typical Hebrew word consists of a pattern and a stem. In most cases the stem is either three or four letters. The pattern is whatever left after you take out the stem, or at least in the simplest cases. Let’s take the word “shalom”, for example, which literally means “peace” or “well-being”, but often just “hi”. There are different ways to write it. The most commonly used one is

שלום

(Read right-to-left.)

However, when learning Hebrew, it makes much more sense to write it as

שָׁלוֹם

Note all the three differences: a tiny dot above ש, a T-shaped mark under it and a tiny dot above ו. The first dot is not very interesting: it’s just that there are two different letters that look almost the same: shin (שׁ) and sin (שׂ). These dots just mark the difference, and normally they are omitted, just like you often omit various diacritics in English loanwords like “fiancee”.

The other two marks are much more interesting. They are vowels. Turns out, Hebrew predates vowel letters, and due to religious reasons it was not feasible to add them later on. So diacritic marks known as nekudot ([neh-koo-DOT], meaning just “dots”) were invented. The T-shaped one is “a”, and the dot above ו is “o”. A funny thing, even though the letter ו (vav) is normally pronounced as “v”, the presence of that dot makes it silent, therefore turning it into a vowel letter (the letter itself is silent, but the dot is still pronounced as a vowel). There is a good reason for this: before nekudot were invented, some consonant letters were used as both consonant and vowel ones. The most commonly used are ו (v/o/u), י (y/i) and ה (h/a/e, but can only be silent at the end of a word, where it typically is silent). But sometimes י stands for “a”, or ה stands for “o” at the end of a word or other weird things happen. This weirdness comes from religious texts too, which can’t be changed, so the language had to adapt to reflect the correct pronunciation.

But that all is annoying and not really fun. What’s important is that this word has a stem, namely ש-ל-מ. Never mind that ם turns into מ and vice versa. ם is just the right way to write מ at the end of a word, and that’s purely a graphical feature specific to just five letters (of 23). But since ש-ל-מ is not exactly a word, the standard forms of letters are used. So both שלום and שלומך have the same stem.

What’s the pattern then? In Latin, it could be written as 1-a-2-o-3. In Hebrew, it’s kind of hard to write because you can’t write nekudot without letters, and all nekudot are a part of the pattern (except the dot from the letter shin, which is actually a part of the letter and therefore belongs to the stem together with the letter). The most common way to write patterns is to put some random stem in it, preferably a one that doesn’t distort the pattern (which is a pretty common occurrence known as gizra [geez-RAH]). The usual stem is ק-ט-ל, which is a bit uncomfortable because its meanings are associated with killing, but it works the best as the letters are very gizra-neutral and don’t wreak havoc on the pattern.

The order of the letters is important. It’s also a very rare thing of the pattern letters to get intermixed with the stem letters. In fact, there is only one pattern where that happens, and there are strict rules for that one. Note, however, when I say “letters” here, I mean full-fledged consonants. וֹ in שלום is no longer a letter in that sense and therefore it jumps in between ל and ם quite easily.

The whole stem-pattern business has enormous impact on the learner. In a random Western language, when you see an unfamiliar word, you can sort of guess its meaning if you know its stem. Say, if you know what “white” means, you can probably guess the meanings of “whiting”, “whiteness” and similar words. Hebrew goes much further because sometimes even apparently unrelated words share a common stem or a pattern. Say, you know that פיגוע [pee-GOO-ah] is a terrorist act. And then you see פגיעה somewhere. You instantly recognize the stem, and knowing that the pattern קטילה [ktee-LAH] usually means some action, but not as intense as the pattern קיטול [kee-TOOL], you deduce that it must be some other bad action, but not as bad as a terrorist act. An assault perhaps, or some other kind of offense. Then you look at the context:

מה לעשות במקרה של פגיעה משריפה?

Even with my poor Hebrew, I can read that roughly as “What to do in a mikra of pgia from fire?” Now I know, as I’m reading this on a news website, that there is a lot of fires in Israel now, probably due to arsons and dry weather combined. Given all that, I’d guess that “mikra” is something like “situation” and “pgia from fire” is something like an arson, and it’s probably an article explaining what to do if you suspect someone of starting a fire or if you witnessed it, or something along that lines.

Now, I’m fairly sure that פגיעה is pronounced [pgee-AH], but I’m not sure at all about מקרה. It could be [mee-KRAH] or [mah-KREH] or anything. The lack of nekudot doesn’t help to figure out the correct vowels, but knowledge of the patterns does. If I knew what pattern that is, I could probably guess pronunciation with enough confidence, just like I did with פגיעה because it’s a pretty distinguishable pattern, thanks to the way how י and ה are placed.

I really just made up all this by just looking at a random news website just now. Now let me consult my dictionary and see what I got right.

First, מקרה is pronounced [mee-KREH]. Almost got it right. I guessed the meaning right from the context, it’s really an occurrence, or a case. “מה לעשות במקרה של” [MAH lah-ah-SOT beh-mee-KREH SHEL] is literally “what to do in case of…” And I would have been even more sure if I knew how the phrase [MAH kah-RAH] (what happened?) is spelled (that’s מה קרה, but I’ve never seen it before, only heard).

Second, פגיעה is a blow (a physical or a moral one), a hit, damage, an injury. And looking at the further text, it seems I was wrong about arsons after all. A more appropriate translation would be “What to do when fire hits?” or “What to do in case of fire injury?”, which kind of makes sense, as I think, because any reasonable person probably already knows that in case of a suspected arson the only right thing to do is call the cops, but many people don’t know everything that should be done in case of fire or fire injury.

Still, as you can see, even as I encountered two totally unfamiliar words, I was able to guess their meanings to some extent.

Thanks to gzarot (plural of gizra), though, this exercise becomes much more complicated. In this case, their effect is minimal (that “e” at the end that I got wrong). But there are cases when a mere presence of a certain letter in a certain position breaks everything. Say, words like מדבר [meed-BAR], מגדל [meeg-DAL] and מערב [mah-ah-RAV] belong to the same pattern, but see how the last one is pronounced? All thanks to the letter ע which doesn’t like “i” before it and the lack of a vowel after it, but absolutely loves the “a” vowel on both sides. Gzarot get even worse with words like שומר [shoh-MER] and גר [GAR] which also belong to the same pattern… or, rather, would belong to the same pattern if it was possible to squeeze the root ג-ו-ר into it. But since it’s impossible (for no reason), the middle letter of the stem just disappears and the whole pattern is changed so drastically, that it’s easier to say it’s replaced by another pattern altogether. Thankfully, gzarot are rules, not exceptions. Meaning that if it works that way with this particular stem and this particular pattern, it will work the same way with another stem/pattern pair that satisfies the same condition. If we take the same “shomer” pattern and the  ד-ו-ר stem, we know it’ll be דר [DAR] and nothing else. Sometimes the rules are ambiguous, though, but they still usually limit the possibilities to two or three.

And yet, with all this weirdness, the most of the language vocabulary suddenly turns from a list of seemingly random words into a nice table of stems (about 4000 of them) and patterns (about 200), and a set of gzarot to learn. That’s an order of magnitude less than tens of thousand words for a typical random language. What’s especially good about it is that once you know a word, it’s easy to restore both spelling and pronunciation. If you remember the word קרה from the phrase מה קרה and then you remember the pattern מגדר, then you may misread the word מקרה as [mee-KRAH], as I did above, but even if you don’t remember how it’s pronounced at least you’ll get the spelling right (without the vowels), so you won’t get [mee-KHRAH] or [mee-GRAH] because you know the stem. And once you’ve seen that type of a word, you’ll figure out the gizra, and then you can apply it to different words as well. Now when I see מפנה, I know it’s [mee-FNEH], and not [mee-FNAH]. Ditto for משנה [mee-SHNEH]. Apparently the gizra here is that when a stem with the third letter י (which often turns into a silent ה at the end, just like here) goes into the pattern of מגדל, the last vowel changes to “e” (before the silent ה):

מִגְדָּל ← מִקְרֶה

(The one dot is “i”, the three-dots triangle is “e”, the two dots are silent in this case, and never mind the dot in the middle of ד).

See how learning separate words turns into learning whole groups of words. What’s even better is that different gzarot often don’t interfere with each other. If I know that ע likes “a” around it and the silent ה “e” before it in this pattern, I can easily read מערה as [mah-ah-REH].

Then there are various suffixes and endings that can be attached to a word, and that could change the pattern as well, but that’s another story. It’s enough to say that there are rules for that too. And learning rules is much more pleasant process than learning seemingly random sequences of characters that are called meaningful words for some reason that escapes me completely.

Why I love Japanese

I absolutely love foreign languages, and I’m also exceptionally bad at them. It took me, what, like 20 years to get my English to this level, and that’s mostly thanks to practice. But I just had to. I used to play a lot of computer games, and Russian translations were so awful that it was easier to play in English even when I didn’t speak it. I used to read a lot of texts about programming, and they were naturally in English too. Then I had to talk to my European colleagues on phone with no interpreter. Then I watched anime with English subtitles because Russian were either unavailable or, again, ridiculously awful. So, yeah, I had to pick some English skills on the way.

Other languages are different. Like most programmers, I’m very lazy. I’d rather make my computer do my work for me, but, naturally, it can’t learn languages for me, and even if it could, it wouldn’t help me either. So… my usual way of learning a language is to find some learning material, ponder over it for a few minutes (or hours, if I feel really stubborn) and then just forget about that particular language for half a year or so. Naturally, it doesn’t work very well.

But… even when things are that way with German, French and Irish, they are just a little bit better with Japanese and Hebrew. Hebrew aside for the moment, I’d like to say a few things about Japanese.

In case you didn’t know, Japanese has two writing systems: kana and kanji. Kana is divided into two subsystems again: hiragana and katakana. Kana is a phonetic system with pretty much one-to-one correspondence between syllables and characters. There are few exceptions, but they are pretty well-defined too. Note that I say “syllables”, not “sounds”. That’s because Japanese doesn’t have separate sounds, so even if you really wanted, you couldn’t make up a word like the famous Russian “взбзднуть”, which roughly reads as “vzbzdnut’”. That’s right, six consonants at the beginning (and as far as I know, some Slavic languages even have words with no vowels at all). In Japanese you only have syllables that sound like consonant-vowel or just a vowel. And there’s also “n/m”, which is a separate syllable that is pronounced as “n” in most contexts and as “m” in the few remaining. This feature of Japanese language makes it sound very beautiful. It also makes it rather hard to adapt loanwords to it (lack of certain sounds doesn’t help either). Now you know why “the world” sounds like “za waarudo”. It goes like this:

  • Change ”th” to “z” because it’s the closest sound.
  • Change “e” to “a” because it doesn’t sound in English like “e” at all, and “a” is again the closest sound.
  • Change “or” to “a” for the same reason. Japanese does have long vowels, though, hence the “aa”.
  • There is no “L”, but Japanese “r” sounds very much like it. But there are no separate vowels, so it turns into “ru”. That’s because the “u” sound is considered the least noticeable vowel (sometimes it isn’t pronounced at all).
  • There is the “d” sound, but, alas, the syllable “du” sounds more like “zu”. That’s why “o” is used as the extra vowel here instead of “u”.

In case you wonder, hiragana and katakana differ only in their appearance, pretty much like printed letters differ from written ones. Hiragana is mostly used for regular writing (mixed with kanji), and katakana is typically reserved for loanwords and design purposes (banners, ads and so on).

And now we’re getting to my favorite part. Kanji. They are originally Chinese, and most of them still look identically to their original counterparts (I know of only one exception). They typically have several different readings, mostly grouped in two groups: original Chinese pronunciation, adapted to Japanese, and Japanese pronunciation, corresponding to the same word in Japanese like it was before there were any kanji at all. That’s why 道 can be pronounced as “dou” (read as “door” because “u” after “o” makes it long) or “michi”. To make things even worse, kanji in names often have totally different readings, which makes it next to impossible to read a Japanese name unless it comes with hiragana transcription known as furigana.

But that was the bad part. The good one is that, unlike most other languages in the world (except Chinese, naturally), Japanese words actually do make sense. Think about it. Does the word “two” make any sense to you? Why “two”? In Russian it’s “два”, which suggests a common origin. Without doing an etymological research, we can hardly say what that origin is. But even if we know it, we still can’t answer the basic question: why on earth does it sound like that? Why not “boom” or “swin”? Surely such a common word must be short, but there is no saying why it should sound or be written this way or that way. In Japanese, there is no reason why the word sounds like it does, but there is a good reason why it should be written like this:

It shouldn’t surprise you much that one, two, three are written as 一、ニ、三. Of course, things are not always that simple. For example, I have no idea why four is written as 四. There is certainly an etymological reason, but who needs one when you can clearly see two strokes in a square, and two squared is certainly four! So unlike Western languages, which lose original word meanings over time, kanji actually gain new meanings, and it’s up to your imagination how many explanations you can find.

It gets even better. Most kanji are actually composed of elements, and every element has its own meaning. There are just a couple hundred elements, as compared to about two thousand kanji in Japanese alone (much more in Chinese).

It makes learning Japanese (well, the kanji part at least) a very unusual thing. Instead of the usual cramming, you may ponder a lot over every character, trying to find new meanings behind it and see its internal beauty. There are many works already done on this topic, for example Henshall mnemonics or a very good book in Russian by Adyl Talyshkhanov. But there’s one thing about them: you gain much more by doing the same work yourself than by reading explanations written by someone else. And even if you do, it’s better to rediscover meanings again and again, rather than write them down once and refer to them each time. I’ve written down a lot of them (in Russian), but hardly remember any. For example, I encountered this word recently:

超能力

The characters correspond roughly to “super”, “ability” and “strength”. The most literal (and pretty appropriate) translation would be “superpower”, as in ESP and all that kind of stuff.

I have no problems whatsoever remembering the 力 part. It’s purely graphical: just imagine a strong man bending his arm to show off his muscles. However, the first two characters often leave me puzzled.

Let’s take 能 for example. It consists of 厶 (I, myself), 月 (month, moon, but Talyshkhanov sometimes refers to it as “meat”) and two of 匕 (which my dictionary lists as “spoon”, but it looks very much like a sitting person as well). Now, Talyshkhanov explains this riddle as “some people have the ability to see plain meat in this kanji, others have the skill to see a romantic crescent moon”. Ability, skill, talent—these are the meanings of this kanji. I don’t like that explanation much, and not just because it lacks “myself”—it can be easily reworded along the lines of “I may have the ability to see a moon here, but those people are just sitting there seeing nothing more than just meat”. But it just doesn’t click either way.

But I seem to have difficulty trying to find other explanations. The good part is, the more difficulty you have, the more time you spend on it, the better you remember it in the end. This process may get very enlightening. Say, forget about sitting people and remember the original “spoon” meaning. Now I can say that I have the ability to eat the Moon with two spoons. This is ridiculous enough to easily remember, but isn’t much enlightening. Or I could think how I worked for a whole month with two spoons to develop some ability. Or maybe I worked on my abilities so hard that I only ate two spoons in a whole month. Repeat that until just looking at this character makes you think of various abilities, even if it takes you spoon-feeding yourself with such nonsense for a whole month.

The first character, 超, is even more ridiculous. It consists of 土 (soil, earth, ground), something that isn’t considered a separate element, but looks suspiciously like a shoe or like a road from the 道 kanji, and then there are 刀 (sword) and 口 (mouth). If that is of any help, the ground combined with the “shoe” makes 走 (to run), and the sword combined with the mouth makes 召, which has ridiculously many meanings, such as seduce, call, send for, wear, put on, ride in, buy, eat, drink and even catch cold. For a laugh, try to imagine how you would do all that things with a sword and a mouth, like seducing someone with your mouth, holding a sword in your hand to make sure that your words come through.

That, however, doesn’t help us understand why 超 stands for transcend or super. Of course, one may think that running is walking super-fast and putting a sword in your mouth transcends all boundaries of reasonable, but it still lacks something. It’s a bit more reasonable to imagine a samurai with a sword, running and shouting something. Such a picture certainly suggests that he transcended a certain level of samurai-ness.

The whole word put together leads us to thinking of a strong superman with a sword running on the ground in moonlight, holding a couple of spoons in his mouth, because apparently it’s his special skill, or something like that.

MVC, MVP and MVVM, pt. 1: The Ideas

There is a lot of confusion going on about GUI design patterns such as Model–View–Controller, Model–View–Presenter and Model–View–View Model. I’m starting this series of blog posts to share my own knowledge and experience with these patterns, hoping to clear up things a bit. I’m not going to dive deep into the history behind these patterns. Instead, I’m going to concentrate on things as they are today.

I’ll start with the ideas behind these patterns. There is one single idea behind them all: separation of concerns. It’s a well-known idiom, closely related to the single responsibility principle, the S part of the SOLID principles. The most clear form of it says: there should be only one reason for a class to change. Separation of concerns takes that to the architecture level: there should be only one reason for a layer to change. The granularity of that reason is different, though. One may say: the Money class should only change if the logic of working with money changes. On the architecture level one would say instead: the view layer should only change when appearance should change (for example, money should now be displayed using a fixed-width font). In particular, the view layer should not change if the business logic changes (money should now be calculated to 2nd digit after the decimal point) or if presentation logic changes (money should now be formatted with 1 digit after the decimal point).

Model–View–Controller

With these ideas in mind, let’s go over the three patterns, starting with MVC. It’s probably the most confusing of them all, and I think it’s mainly because separation of concerns is not complete in MVC.

mvc

To add to the confusion, there are many variations of MVC, and there is no single agreement on what exactly the components do. The view is the easiest part: its job is to display things and receive interactions from the user. You can’t really separate these two concerns: how would you separate displaying text that the user is editing and actually editing this text? There should be a single graphical component that does both of these things. You can do the next best thing, though: delegate user interactions to another component. And here is where the controller comes from.

The controller receives user interactions from the view and processes them. Depending on the interface between the view and the controller you may be able to reduce coupling between them, and that’s a good thing. Suppose your view is implemented with Swing, and there is the apply button. Instead of making the controller implement ActionListener, implement it inside the view and delegate the apply button click to the apply method of the controller, which is UI-agnostic (it doesn’t depend on Swing at all).

That was the easy part. But what happens next? The controller acts on the model, which contains the actual data the application works with. Then, at some point, it may be needed to display the updated data back to the user. Here is where the confusion starts. One possibility is that there is the observer pattern acting between the view and the model. In this case, the view subscribes to certain events of the model, and the model either sends the updated data to the view (the push model of the observer pattern) or just events (the pull model). In the latter case, the view needs to pull the necessary data whenever it receives the appropriate event.

Note that even though the model sends data to the view, it has no idea of its existence because of the observer pattern. This is especially important if the model is in fact the domain model, which should be isolated as much as possible. It should only communicate to the outside world through clean interfaces that belong to the model itself.

Another variation of the MVC pattern is often seen in web frameworks, such as Spring MVC. In this case, the model is a simple DTO (data transfer object), basically a hash map, easily serialized into JSON or something. The controller prepares the model and sends it to the view. Sometimes it’s just a matter of passing the object inside a single process, but sometimes the model is literally sent over the wire. This is different from a typical desktop observer approach where the controller doesn’t even know anything about the view. To keep this coupling loose, the controller often doesn’t send the model directly to the view, but rather sends it to the framework which then picks up an appropriate view and passes the model to it.

web_mvc

What makes this pattern especially confusing is that the model is no longer the domain model. Rather we have two models now: the M part of the MVC pattern is the data transfer model, whereas the controller acts on the domain model (maybe indirectly through a service layer), gets back the updated data, then packs that data into a DTO and passes it to the view to display. This very idea of the data transfer model is exactly what makes this pattern so suitable for web applications, where the controller may not even know in the advance what to do with the data: you may have to wrap it into HTML and send to the browser, or maybe you serialize it into JSON and send it as a REST response.

Either way, one problem with MVC is that view is too complicated. One thing about UI is that it tends to be both heavyweight and volatile, so you usually want to keep it as clean as possible. In MVC, view doesn’t only display data but it also has the responsibility of pulling that data from the model. That means the view has two reasons to change: either requirements for displaying data are changed or the representation of that data is changed. If the model is the domain model, then it’s especially bad: the UI should not depend on how data is organized in the domain model. If the model is a DTO model, then it’s not that bad, but it still can be changed, for example, to accommodate the need for a new view (or a REST client). Still, MVC is often the best choice for web applications, and therefore is the primary pattern of many web frameworks.

One major disadvantage of MVC is that the view is not completely devoid of logic, and therefore it can be hard to test, especially when it comes to unit tests. Another disadvantage is that you have to reimplement all that logic if you’re porting your view to another tech (say, Swing to JavaFX).

Model–View–Presenter

One natural way to improve MVC is to reduce the coupling between the view and the model. If we make a rule that all interactions between the view and the model must go through the controller, then the controller becomes the single point for implementing presentation logic. That’s what we call a presenter. The term presentation logic refers to any kind of logic that is directly related to the UI but not to the way how the components actually look (that’s the view’s responsibility). For example, we may have a rule that if a certain value exceeds a certain threshold, then it should be displayed in red color. We split this rule into three parts:

  1. If a value exceeds a certain threshold, then it’s too high.
  2. If it’s too high, then it should be displayed in a special way.
  3. If it’s too high, then it should be displayed in red.

The first part is the domain logic. It could be implemented, say, with an isTooHigh method, but it really depends on the domain. The second part is the presentation logic, and if it looks like a generalization of the third part, that’s exactly what it is. The presenter knows from the model that the value is too high, and therefore, passes it to the view with some kind of Status.TOO_HIGH enum constant. Note that it has no idea of colors yet. It’s the job of the view to actually map that constant to a color. Or maybe it could be something else than a color, like a warning sign next to the value.

mvp

In the MVP pattern, the view is completely decoupled from the model. The presenter is something similar to the mediator pattern. In fact, if the view is implemented as a set of independent graphical components (like multiple windows), and the model also consists of multiple objects (as it almost always the case), it would be exactly the mediator pattern.

Unlike MVC, there is no observer pattern between the presenter and the view. The reason for this is that the view contains so little logic there is no place for any event handling there, except for view-specific UI events (button clicks etc.). It’s the presenter’s job to figure out when to update the view and do so by calling appropriate methods. These methods typically belong to an interface fully defined by the presenter, which is an excellent example of the dependency inversion principle (the D in SOLID). The presenter doesn’t depend on any technologies the view uses. Well, in theory at least. For example, it would be very tricky to implement exactly the same interface with Swing, JavaFX and HTML. How do you call methods on HTML? You could have some server-side object that sends the data to the browser using AJAX or even Web Socket, I suppose, but it would be very tricky and at the same time not as powerful as MVC, where controller is free of presentation logic and therefore can be shared between views with different presentation needs (such as HTML and JSON).

The positive side is that since all presentation logic is in one place, porting to another view tech is a breeze. You just reimplement your view interface with another tech, and you got it. Well, that’s at least in theory. In practice you may run into various problems. Threading, for example. Who is responsible that view methods are only called in the appropriate threads? Should the view enforce that? Probably yes, because the presenter has no way of figuring out which thread is right if it has no idea what GUI framework is used in the first place. But that imposes additional burden on the view. But still, MVP is probably as close as you can get to the perfection of total independence from the GUI framework used.

The bad news is that presenter now contains a lot of boilerplate code. It was a part of the view before, so it’s not like it became any worse than it was with MVC, but still it’s always a nice idea to get rid of as much boilerplate code as possible. That’s where MVVM comes into the picture.

Model–View–View Model

mvvm

MVVM is basically the same thing as MVP, except for one major difference. In MVP, the view only delegates user interactions to the presenter. Whenever the feedback is needed, it’s the presenter who takes action. It does it by literally calling methods on the view such as displayFilesList(files), setApplyEnabled(true), setConnectionStatus(ConnectionStatus.GOOD) and so on. That’s boilerplate code. With MVVM, the presenter becomes the view model, that is, a model that provides access to the ready-to-display data through the observer pattern, much like in desktop MVC. Except that now the view model can really prepare that data for display by filtering, sorting, formatting etc. So whatever presentation logic was in the view in MVC, it’s now in the view model. And while in MVP the presenter pushed that data from to the view, in MVVM the view pulls that data from the view model. This sounds like we’re adding responsibility to the view, and that’s a Bad Thing, right? Well, to a certain extent, yes. But the point is, this responsibility is typically almost entirely implemented by the framework. This is done through data binding, where you just specify that this component should display that property of the view model, and that’s basically it.

When your framework doesn’t support data binding, it’s usually a bad idea to use MVVM because you’ll essentially be moving the boilerplate code from the presenter to the view, which is indeed a Bad Thing. And even if you have data binding, it’s usually not that simple. Sometimes you have complicated structures to bind. Sometimes the order of updates is important and you have race conditions in your UI. Sometimes you have values of custom types that are tricky to display directly, you need to employ some sort of converters for that.

The good part is that with MVVM you typically only have problems when you have a non-standard situation. For most cases, it really decreases the amount of boilerplate code and displaying a person’s name in a text field becomes as simple as writing Text=”{Binding Person.Name}” in XAML.

Moreover, delegating user interactions is often implemented with data binding too. Well, as I say “often”, I really can’t think of any other MVVM implementation than .Net/WPF, so I guess it’s 100% of all cases, even though there is only one case in total! Nevertheless, using the command pattern, we can expose possible interactions as properties of the view model. The view then binds to them and executes appropriate commands when the user does something. One big advantage of it is that we can easily change these commands dynamically and the view will automatically update its interactions.

When choosing between MVVM and MVP, it’s important to consider several factors:

  • If your framework doesn’t support data binding, MVVM is probably a bad idea.
  • If it does, then how likely that you’ll want to switch UIs? How painful is it likely to be?
  • How difficult it would be to port your application from MVVM to MVP or MVC or vice versa?

All things being equal, it’s often the case that reimplementing the view interface for a new framework in MVP pattern is about as hard as switching from MVVM to MVP or whatever. In this case, it’s probably worth to use MVVM if that’s the thing with your framework. The same really goes about using MVC. When your framework offers you MVC, you probably don’t want to force yourself to use MVP instead unless you really plan to switch frameworks and design for it beforehand. Say, you’re using Swing right now, but you know you’ll have to move to JavaFX within 5 years.

One last thing to note is that it is possible to combine these patterns, although in most cases it’s likely to lead to over-engineering. For example, if your framework forces you to use MVC, you can really turn your controller into a view model, and then consider the whole view–view model part to be just a view for the MVP pattern. So when user does something, the view delegates that to the controller, which immediately delegates to the presenter. When the presenter gets updated data from the domain model, it sends that data to the controller (using a clean interface), which then stores it locally and fires an event to the actual view which pulls that data to actually display it. Sounds crazy enough as it is, doesn’t it? But sometimes it may be worth it, only experience can tell you. It’s probably best to start with the simplest thing possible, and complicate things only when you actually need it.

That’s it for now. I plan later to demonstrate all three patterns with a simple application. I’ll probably use Java for that, even though implementing MVVM would be tricky. But there is some limited data binding in Java, so it could actually work, if only for demonstration purposes.

Hide and show JTable columns, pt. 2

Now that we’re done with the menu, let’s make it work. The simplest test I can think of clicks on a menu item and checks that the number of visible columns has decreased:

I’ve changed getMenuItems to accept JTable instead of JPopupMenu to make the code less verbose. This test obviously fails as the menu does nothing yet. On one hand, the fix is not so simple. We need to add appropriate listeners to the items. On the other hand, something as silly as this will do the trick:

Okay, this is really silly. But our test passes now, and that means the problem is with our test. Why not use a data provider to parameterize our test?

This is better. Now it fails again. If you’re wondering about DP_COLUMN_INDEXES, it’s just a constant set to “columnIndexes”. Why bother? Because I don’t like hardcoding function names. What if I need to rename it later? Like this, I can name the provider function anything I want. Of course, it’s better to rename and change the constant as well, just to keep it consistent. But that’s just three changes: function name, constant name and the constant literal itself. And even if I forget to touch the constant, nothing breaks.

OK, so now the fix looks like this:

But it’s still obviously wrong. Well, maybe not so obviously, but remember that Swing has two coordinate systems: the view and the model. Columns can be rearranged in the view, so the mapping can change, even though it’s the identity by default. So we need yet another test. But first, we need to decide whether we want the menu items to rearrange when the columns are rearranged. I think not. First of all, it’s too much of a hassle. And it can be confusing for the user too. Besides, the menu contains all columns, and the view only some of them. Where do we put the hidden columns in the menu if they are not a part of the view order? So let’s keep them in the model order.

Now I have refactored setup code into a separate method. I haven’t annotated it with @BeforeMethod because it’s not a universal test fixture: the install method checks that the menu is not null, so obviously we can’t use it even before the test is started. I’ve introduced an @AfterMethod cleanup method, though (not shown), that just sets everything to null, just to be 100% sure that one test can’t possibly use something created by another.

Now to the fix:

I actually got it wrong on the first try—put the conversion call outside the listener. That froze vIndex forever, which is obviously not what we want. Note that this one of the cases where Hungarian notation is tremendously useful: both model and view indexes have the same type, so Hungarian notation lets us see immediately what kind of index we’re looking at.

Now I don’t really like the looks of the install method. And we haven’t even got to showing hidden columns. So let’s refactor it a little bit.

This is much better. More methods, the code is much longer, but each method is pretty clean and readable. Note that I’ve created a field for the JTable. It was captured by the lambda anyway, so I haven’t actually introduced any new state here. Just moved it from the lambda to the top-level class.

Now let’s check that the columns are properly shown (which, of course, they aren’t).

This fails, but with a very obscure message: java.lang.ArrayIndexOutOfBoundsException: -1. Why? Because the second click is trying to hide an already hidden column. Can we do something about this message? Well, not by modifying the testing code. But we can modify the hideColumn method! What should it do when the column is already hidden? Nothing? Or throw an exception? And should we even bother at all? Probably not at this point. Later on, we may want to make that method public or add some other API to hide and show columns programmatically. Then we’ll have to solve this problem. For now, let’s bear with the obscure message and fix the class.

The change is not trivial. I had to add a hash map of removed columns so we can show them later. The key is the model index.

The action listener became a bit large, so I should either refactor it into an inner class or make it smaller. It’s not large enough to justify a class, so I’ll opt for another private method:

This is better.

We got it almost working! One last obvious thing is that we append the column to the end when we show it. This is not good. But where should we put it? The order of columns could have changed since we hid it. There is no perfect solution, so I’ll choose a simple one: put it where it belongs if the columns are not rearranged, otherwise put it somewhere reasonable. With this vague requirement we only need to test that the column reappears in its place if we keep the model order, and that it reappears at all otherwise.

Let’s start with the simple case.

And the fix is:

Now this can easily break if the model index is not a valid view index. How? Well, imagine that we removed some other columns and the column count is now very low. If the column removed was somewhere near the end, its model index may be very well outside the bounds now. Let’s test it.

The fix:

At this point I felt like this thing is going to work now. So I ran the demo I created last time. But as I tried to hide a column I got this:

The funny thing is, there are no our methods in this trace! That shows clear enough that TDD is not a magic silver bullet. Even though from our tests we expected that our code should work fine at least under normal circumstances, it crashes immediately. Why? After investigating a little bit, I think it’s because of a subtle bug in Swing. When we right-click on a column to show the menu, it thinks we’re about to drag that column. Indeed, dragging with right mouse button works, sort of. Sometimes it leaves the column floating in mid-drag. Then, after the column is removed, dragging breaks because the column has no valid view index (hence the index out of bounds exception).

There are different possible workarounds. We could try to install a custom table header that would override the getDraggedColumn method and return null if the column is hidden. But that would prevent users from using their own header. Of course, we could wrap the existing header into our own. But that would require delegating all of its methods to the wrapped instance, and there is a lot of them.

Another possible way is to consume the right click to prevent it from dragging anything. Alas, the default event handler is the first in the line. By the time we consume the event, it’s too late.

A really silly way is to just set dragged column to null whenever we hide it. It’s so simple and stupid it might actually work. Let’s try it.

Yay! It works, and with no visible glitches too.

At this point I’d like to conclude this self-educating tutorial. Of course, there is a lot of things still to be done, such as: provide a way to uninstall it, check what happens if we install it twice on the same table or try to reinstall on another, provide an API to show and hide columns from code, prevent the user from hiding the last visible column (or the header will disappear and it will be impossible to get them back). These are just the ones I can think of right off the bat.

For those interested to improve it or study the full history of its evolution, the code is available at

https://github.com/stachenov/jtable-column-selector

The point at which this tutorial ends is tagged tutorial-pt2.

Hide and show JTable columns

Swing is getting old, but is still widely used. To my surprise, it turns out that its JTable doesn’t support hiding and showing columns at user’s whim. Well, it’s time to fix that!

Note that a similar work has already been done. So the purpose of this post is mainly educational. I’m going to do it using TDD and keeping the code as clean as I can. But first, it’s time for some design.

What we need is a menu. So it looks reasonable to extend JPopupMenu. However, we need more than that. We also need some boilerplate logic that will bind that menu together with JTable. We can extend JTable to do that, but that doesn’t sound like a good idea because that would prevent anyone with their own derivatives of JTable from using our code.

So it looks like ideally we would like to have a class that we could instantiate and install on a JTable to handle all that logic. Perhaps it will use a separate class for a menu, perhaps some other classes. Let’s not bother with these details for now. Instead, we should think of a name. JTableColumnSelector sounds fine: the J hints that it’s a Swing class, and it openly tells us that it is used to select columns. Maybe it is not very clear that it hides or shows columns, but JTableColumnHiderShower just doesn’t sound right, and besides, shower is something entirely different.

Before I begin, I should mention that for TDD I’m using TestNG, AssertJ and Mockito. That’s my usual set of tools.

The first TDD iteration looks rather stupid: write a single line test with new JTableColumnSelector(), then make it compile by creating an empty class. At this point I’m making an important design decision: by choosing to use a no-args constructor, I’m making life easier for anyone willing to extend my class. Because I’m going to have a separate install method instead of passing a JTable directly to the constructor, it is guaranteed that install will only be called after the object is fully initialized.

Speaking of install method, we need another test:

What I like about Swing here is that it doesn’t really care that we’re calling its methods from a random testing thread. As long as it’s just one random thread, it runs just fine. What I don’t like about it, though, is that this very same feature makes it fail mysteriously at random moments when you call its methods from a wrong thread, thus violating the rule of repair terribly. Useful for testing, dangerous in production, as it often happens. Ideally, there should be a way to control this behavior, something like -Djavax.swing.allowCallsFromAnyThread.

But let’s get back to TDD. To make the test above pass, we need the appropriate method. And I also correct the constructor javadoc while I’m at it:

Now we need to test that it does what it should do. What should it do? Well, for one thing, it must create a popup menu on the table header, so let’s test it:

It fails. Good! Now let’s fix it:

Now we need to check that the menu contains… what? Obviously, a list of items. There should be as many of them as there are columns in the model. Wait, our table doesn’t have a model yet. So maybe here is where we should start using Mockito:

Here, I set A_REASONABLE_COLUMN_COUNT to 10. The test fails, but isn’t terribly readable, so I’m going to refactor it a bit first.

This looks a bit better. Now we need to make it pass.

OK, what next? I’m worried about two things now. First, the model might be null. Will getColumnCount() properly return zero or will it just throw a NullPointerException? And is it even a good idea to ask the table about column count? Shouldn’t we ask the model instead? What if some columns are already hidden by some other code? Should we display them in our menu? Let’s assume for now that we want to list all model columns. But then the code is wrong and we need a test that shows it.

Another thing I’m worried about is that we incorrectly created JMenuItems, while we should have used JCheckBoxMenuItem or whatever it’s really called. But that should become apparent later, when we start selecting menu items. So let’s deal with column counts now.

It fails. Cool. Let’s fix:

Now we have a real problem if model is null. We need another test for that:

Hmm… It passes! Why? Oh, I forgot that the model can’t be null! The table creates a default empty model for that case. Good. I hate nulls. But then we need to rename our test. installsProperlyWhenTableHasDefaultEmptyModel is a bit too long, but descriptive enough, so I’ll keep it.

Cool. Now let’s get back to install test. We need to check that all menu items have the right labels. But first we need to make our mock return that labels. Unfortunately it isn’t terribly easy to do with Mockito. No, wait, it’s actually easy, but not very elegant:

Maybe I should have used a real model instead of the mock. But it doesn’t that bad, so I’ll keep it like this for now. Only refactor this ugly class into a nested static class.

Now we need a couple of helper methods to extract column names from both the model and the menu. The lists should be the same. I’m feeling functional, so these methods turned like this:

And the new test is:

This is appended to the end of install, but I’m not repeating everything again and again. The proponents of the one-assert-per test idiom are probably cursing me now, but I think I’m doing the right thing here: I’m still testing that this thing installs properly. If I need three asserts for that, so be it!

Of course the test fails, and with a clear message too except that it’s too long. So I’ve changed A_REASONABLE_COLUMN_COUNT to 3. Now we have to fix it the test. Just one line has to be changed:

And now for the last piece of installation. We need to check that all of the menu items are selected. We need another helper method for that. Or maybe I’ll refactor this one:

And the test is now:

Oops! Looks like JMenuItem has isSelected method too, just like JCheckBoxMenuItem or whatever. Well, for now let’s just fix the test:

This goes into the loop of the install method. OK, what about the wrong class? We could just continue and then let it surface later, perhaps during manual testing. But I find it rather silly. Since I’ve noticed it already, why not fix it now? Changing JMenuItem to JCheckBoxMenuItem everywhere in the test seems to do the trick. Now the test fails with a clear message: javax.swing.JMenuItem cannot be cast to javax.swing.JCheckBoxMenuItem. Cool.

That’s it for today, except that I want to see how it looks on the screen, so I create a very simple demo:

Aaaaaand… it works!

menu

Next time we will add some logic to make it really work and do what it’s supposed to.

Getting started with JavaFX 8 custom controls

I need to develop a custom control for JavaFX 8. Unfortunately, most of the tutorials concentrate on the FXML way to do it, but I need to code in some custom painting.

How would I do it in Swing? Extend some base class and override paint. That’s it. In JavaFX, the right way seems to be overriding two classes: the control itself and the skin. OK, this actually looks like a good idea: the control is responsible for behavior, and the skin is responsible for the painting. So let’s look at the skin API:

What? Where is the paint method? According to the docs, getSkinnable() simply returns the associated control, dispose() detaches the skin from the control and getNode() “Gets the Node which represents this Skin”. What the…? So we have one node that is the control itself and another node which is the skin? I hope we don’t need to skin the skin, considering that it’s a kind of node itself!

After looking at some examples, I got the general idea. The skin is just a bunch of nodes, and getNode() just returns the root node. If you want to really customize your paining, you can always use a canvas as a skin. But I decided to try to use some shape nodes instead.

OK, I can create some shapes, put then into a Group, for example, and then what? The skin obviously needs to handle resizing. But how does it know when to resize exactly? I could just subscribe to the control’s width and height properties (and unsubscribe in dispose). But that feels ugly. Still, Han Solo himself does exactly that, so maybe it’s the right way after all?

After trying a lot of various things, I still couldn’t get it right:

  • If I just put my shapes into a Group, the control doesn’t resize properly.
  • If I put my shapes into a Group and inherit from SkinBase instead of implementing Skin, the control does resize, but…
  • All shapes are centered and I can’t position them. Looking at SkinBase sources, turns out it’s hardcoded.
  • If I draw a vertical line of length exactly equal to the control’s height, the control automatically increases its size by one pixel at each repaint. So if I keep resizing it horizontally, for example, it keeps growing vertically forever.

All of that didn’t make any sense. After further studying SkinBase sources, I got a feeling that a skin acts like a layout manager. That is, it’s responsible for managing the relative positions of its children. It is done by applying the appropriate transformations the result of which can be queried by calling getLayoutX() and getLayoutY() on the components.

Another thing is that SkinBase cheats around getChildren() being protected in the Control class. That allows it to directly manipulate the children of the control—no Group needed.

So in the end I concluded that:

  • A skin is best implemented by inheriting SkinBase.
  • To add components, just call getChildren().addAll(children).
  • To position the components needed to draw the skin, override layoutChildren. From it, call layoutInArea for every child that needs to be positioned.
  • All shapes should be drawn in an imaginary coordinate system that is tied to the shape itself. If you need a line, you might as well start it from (0, 0). layoutInArea will move it to the required position anyway, so the lines (0, 0)–(10, 10) and (10, 10)–(20, 20) will look exactly the same in the end.

The resulting control prototype is this:

The resulting graphics:

bvn_prototype

As you can see, it resizes nicely and the lines are positioned exactly as I want them.

P. S. Further prototyping revealed that it still resizes randomly sometimes, especially as I update values and/or resize window with lots of controls in it. The reason is that by default, SkinBase calculates preferred width/height based on preferred widths/heights of its children. The problem is that preferred width/height of a primitive equals to its actual size (since it’s not directly resizable). Therefore, once a control is resized, its preferred size is now different. If it was the same size as other controls before that, not only it’s no longer the case, but the preferred sizes are different, so layout gives different sizes to different controls. This is repeated on each resize, which leads to a funny “rich get richer” scenario where bigger controls are given more and more space because their preferred size is greater. This issue is fixed by overriding computePrefWidth/Height to return something sensible.

Replacing javadoc for a Maven artifact

I was playing around with a library depending on the JMS API. It downloaded geronimo-jms_1.1_spec-1.1.1.jar as a dependency. Unfortunately, this JAR goes with a javadoc JAR that is virtually empty! It is actually there, but I couldn’t find anything useful in it. And NetBeans IDE insists on displaying javadoc from nowhere else.

Turns out it is quite easy to replace this abomination with docs from the Java EE SDK:

  1. Download the JDK.
  2. Pack the contents of the glassfish4\docs\api dir into a ZIP (the root must contain the package-list file).
  3. Rename it to geronimo-jms_1.1_spec-1.1.1-javadoc.jar.
  4. Move it to %USERPROFILE%\.m2\repository\org\apache\geronimo\specs\geronimo-jms_1.1_spec\1.1.1\.
  5. Nuke the geronimo-jms_1.1_spec-1.1.1-javadoc.jar.sha1 file there, just in case somebody checks the hash and finds out it’s wrong. Or recompute it and edit the file if you feel like it, but it seemed to work fine for me without the file.
  6. Restart the IDE and enjoy the well-written docs.

Of course, it should work just as well with any random JAR file. Of course, Maven can re-download the file, but why should it? Unless you move to another version, everything should be fine.

TestNG and NetBeans: testing exceptions with externalized messages

It all started with two things that should have been obvious for me for a long time:

  1. Every message in a program should be localizable. For Java programs, that means externalized using a resource bundle. And that includes exceptions. Even if those are never shown to users (it’s debatable whether it’s a good or bad idea), keeping them separated from code is still a good idea. For one thing, it makes documenting error messages much easier!
  2. Every unit should have a unit test. In the extreme case, adhering to XP/TDD principles, those should even be written before the actual code.

Now, I’ve been doing unit testing for quite a long time using JUnit, but I never got around to externalizing messages because our software is used internally (and nobody cares). Now for my open source project (ain’t giving a link because it’s nothing there yet) I decided to try TestNG because of its very nice parametrization of tests, and at the same time externalize messages (because who knows, maybe someone someday will want to translate it).

Turned out that these two things don’t mix easily. Here is a short summary of what needs to be done to get everything running. I’m using NetBeans and Maven, but the approach itself may be applied to any setup that uses TestNG and resource bundles. If you’re experienced with your IDE and TestNG you may wish to skip to step 4, where I explain how to use annotation transformers for testing localized exception messages.

Step 1. Configuring NetBeans

This one is tricky for current NetBeans version which is 8.1 and current Maven Surefire plugin version which is 2.19.1 . Assuming you’ve got everything installed (bundled Maven will do), let’s start by creating an example project. Press Ctrl+Shift+N and select Maven—Java Application (the simplest project that can be created). Choose location, sensible group id like name.yourdomain or name.yourdomain.testproject, sensible artifact name like test, and a sensible package name similar to group id, like this:

nb1 nb2

Now switch to the files tab and create a new folder under src called test. Create a subfolder in it called java:

 

nb3

Now it should look like this:nb4

Switching back to the projects tab, you’ll now see the Test Packages element in the tree:nb5These steps were needed to get on with the TDD approach, creating the first test before coding anything. So far it is all easy as long as you follow the Maven conventions (that’s why it’s src/test/java and not something else, this is just a magical incantation). Now create a package under Test Packages with exactly the same name as the source package (name.tachenov.test in my case). Create a class there, say, MyClassTest or MyClassNGTest (both names will allow you to use Ctrl+Shift+T to navigate between MyClass and the test, once both are created) which should look like

Now it doesn’t even compile for two reasons: there is no MyClass, and, which is far more serious, NetBeans has no idea what @Test is. So ask it to create a stub for MyClass inside the source packages (which is a nice feature available since NetBeans 8.1) and add dependency for TestNG.nb6

nb7

Note that I set Scope to test because we obviously don’t need a testing library unless we’re testing. Now this step is somewhat tricky because if you used NetBeans to generate tests in a regular way (code-first) it would automatically add the TestNG dependency… only it would pick up some version NetBeans thinks is right. Well, turns out you need slightly better than that! The version that NetBeans picked doesn’t work quite right with other tools we need.

Now add import for org.testng.annotations.Test and hit Alt+F6. You should see something like

nb9

OK, TDD step 1 complete! We’ve got a failing test. Now we have to fix it! Once you do something like this the test should run fine:

At this time, even if you screw something up, the test will probably run fine nevertheless. Things start to get weird a bit later.

Step 2. Testing exception message

Now we’ve got to break the test again:

Let’s fix it:

Now you have this bad feeling about copy-pasting a message like that. Not only it’s in our code, but it’s in two different places! What if we want to change it? What if we want to translate it? Although Java provides a weird getLocalizedMessage() method for exceptions, it seems to be a real pain to get it working because there is no way to set that localized message! So might as well just localize the non-localized message, even though it feels weird, but that’s what Brian Goetz himself actually recommends!

Step 3. Externalizing the message

Without touching the test, let’s externalize the message in our class. That’s allowed by TDD since it’s the refactoring step: we aren’t changing any logic, we only moving things around.nb10

In the internationalization dialog, press Select, type in a reasonable name, say, “exceptions”, and then press Create New:nb11

Now enter a reasonable key for the message, say, MyClass.objectIsNull, and press Replace and Close.

nb12

After a bit of further refactoring (extracting constants, adding imports) you should get something like this:

One last step is to move the newly created exceptions.properties from src/main/java to src/main/resources, under the same package that it was. Your file structure should look like this:

nb13

This is needed because Maven looks for resources in src/main/resources, but NetBeans created our bundle in src/main/java. So we fixed that and run our test again. We see that it passed, so it’s time to refactor the test.

Step 4. Making the test work with externalized messages

Our first idea may look like this:

We face two problems here. One is that EX_OBJECT_IS_NULL is private. Well, no big deal—just make it package private. Feels weird exposing internals just like that, but package private is still private, and it’s just a constant, so no harm done!

The other problem is far more serious. We get the “element value must be a constant experession” error. Makes sense, since we need it at compile time! But how on earth…? That’s what I asked on Stack Overflow. Thanks to the quick answer I got there, I was able to implement a very nice solution. Like the answer says, create a new annotation type. I call it ExpectedExceptionMessageKey.

And create a class called, say ExceptionRegExpTransformer in our test package.

Now our test should look like this:

I intentionally left expectedExceptionsMessageRegExp there, but changed the message. This allows us to check whether the new way of testing really works. Turns out it isn’t! Well, no big surprise since we never told TestNG to actually use our annotation transformer! At this point, it would be really nice to have it injected magically in our class by using some sort of @AnnotationTransformer annotation on the transformer class. Alas, there is no such magic! Or at least I haven’t found any. So we have to configure TestNG manually through the Surefire plugin. Open pom.xml under Project Files in the Projects view. Insert something like this after </dependencies>:

Whew. This doesn’t look neither elegant, nor short, nor intuitive. For some reason NetBeans stops auto-completing tags under properties, so you actually have to type that by memory, although by that point it’s intuitive (property/name/value—makes sense). The argLine tag is only needed to avoid an annoying warning about encoding.

The important part here is version 2.18.1! At the time of writing the latest version is 2.19.1. NetBeans 8.1 uses 2.10 by default for whatever reason. But if you specify 2.19.1, you get no beautiful green test results window! That is a known bug. Another known bug is that if you use an older version of TestNG (see step 1), for example, 6.8.1 that NetBeans 8.1 uses by default, you may get a “test skipped” window with exceptions in the output window saying that your transformer class can’t be loaded. It doesn’t mean that’s there’s a problem with your class! It means that those versions don’t work well. By experimenting, I found that TestNG 6.9.10 with Surefire 2.18.1 work perfectly.

Step 5. Parametrizing messages

We’re almost done. But sometimes we want our message to contain parameters. Java provides a reasonable way to do it by using MessageFormat. Let’s break our TDD thing here and start with modifying the class (or just consider it refactoring):

And the resource bundle is now

The double quotes are needed to avoid actual quoting of the {0} string, otherwise the message would be literally “The {0} parameter must not be null”, which is obviously not what we want. This is a confusing syntax, but it’s there due to historical reasons.

Now if we run our test, we find out that our “refactoring” broke something. But we didn’t break the class. We broke the test! It is now expecting the message to be exactly what is in the resource bundle. At this point we need to decide whether to test that the message looks like what it’s supposed to look like or that is exactly what it’s supposed to be. What if our test method itself is parametrized? What if we test for IllegalArgumentException and pass various invalid values? Do we need to check that the message actually contains the invalid value? We probably do, but that is, unfortunately, impossible to achieve with annotation transformers. The reason is they do just that—transform annotations. And that happens only once. So if our method is called 200 times, it will have the same annotation over and over again. So it would expect the same message. In this case, maybe it’s simpler to just do try-and-catch and check the message manually with assertEquals (and add fail in case there is no exception).

But if we need to check that the exception looks like what we expect it to look, then there is a solution. To do it right, we really should have two annotations, like @ExpectedExceptionsMessageKey and @ExpectedExceptionsMessageFormatKey. And the second one should really parse format in a manner similar to how MessageFormat.applyPattern does it. But we can probably get away with just this ugly hack for some time:

When will it break? Well, obviously when a real message, not a message format, contains something like {0} or a double quote. But, really, how often do we see those? And if it ever happens, we can easily fix it, probably by another ugly hack.

Another case when it will break is if the format is something more than just an argument number. But then again, even though we often see those in UI messages, exception messages are usually much simpler, along the lines of “Value {0} is invalid” or “Couldn”t open {0}: {1}”.

But if you feel like it, by all means, do it right! I’ve shown you a great tool, it’s up to you how to use it!

Given 12 coins, find one that is lighter or heavier

This is a problem of a well-known type: you’re given some coins (balls, rings), one of them is lighter, heavier, or maybe it can be either lighter or heavier. You need to find that one using no more than some specified number of weighings. In this particular example we have 12 coins, one of them is forged and may be heavier or lighter, we don’t known which. We need to find it in no more than 3 weighings.

In simpler problems, like when you’re given 8 balls and one of them is heavier, and we’re limited to two weighings, we can often succeed using brute-force approach. Try splitting them 4/4, then you quickly figure out that you can’t find one among 4 in one weighing. Well, just try a 3/3 split and then you’re done.

With 12 coins it is not so simple. You could guess that 4/4/4 first split is a good idea, but then you could spend hours trying to figure out the rest. So a smarter approach would be useful. And this is exactly what I’m about to show. But first let’s think about bounds.

Lower bound of the number of weighings

What is the lower bound of the number of weighings for this problem? There are 12 possible answers and each weighing gives us one of the three possible results. This leads to a ternary decision tree that represents our algorithm. To minimize the number of weighings we should minimize the height of the tree by balancing it out. The height of such tree is \lceil \log_3 12 \rceil=3. Makes sense. But only we assume that our algorithm only tells us which coin is forged without actually determining whether it’s lighter or heavier. Such an algorithm is hard to imagine, and if it gives us the complete answer, then there are total of 24 answers. Not that it changes the lower bound, though, as \lceil \log_3 24 \rceil is also 3.

Note that it is only a lower bound. It may or may not be actually reachable, and that’s much harder to prove (but the proof does exist with exact numbers). Obviously if we can find an algorithm that works, then it’s reachable. But if we can’t find one, it doesn’t mean that it doesn’t exist. Unless we’ve actually brute-forcibly tried all of them. It isn’t that hard for small problems, and I’ve actually done it for 12 and 13 coins. Turns out the lower bound is reachable in case of 12 coins, but in case of 13 coins it’s only reachable if we don’t need to know whether the forged coin is lighter or heavier. So even though that \lceil \log_3 26 \rceil = 3, we can’t build an algorithm that finds all 26 answers.

A heuristics for building the right solution

How do we produce an algorithm for a given problem without brute-forcing it? I hereby present a heuristics that gives three hints as to what to do next.

U -> L, H, G; L -> G; H -> G

Possible coin transitions

Let’s start by partitioning coins into four groups. Initially all coins belong to the group U, which is the group of coins we know nothing of. Then there are groups L and H which contain coins that may be lighter (but not heavier) and vice versa. If we weigh some coins from U and they don’t balance out, then the heavier pile goes to H and the lighter one goes to L. The rest of the coins, which did not participate in the weighing, are obviously genuine so they go to the last group, G. When we weigh suspicious coins with some genuine ones and they balance out, then the suspicious coins go to G no matter which group they belonged to.

Our goal is to maximize the information gained by each weighing. And since we have no idea what the result of the weighing will be, we should try to maximize worst-case results, much like in the minimax algorithm.

But how do we measure information gained? Obviously each coin promoted from one group to another is something. But if a coin jumps from U to G directly, it’s even better than a coin going from U to L or H, or from L or H to G. So here is the first hint:

We should pick a weighing that maximizes the minimum of N_{U \rightarrow L} + N_{U \rightarrow H} + N_{L \rightarrow G} + N_{H \rightarrow G} + 2N_{U \rightarrow G} for all possible results of a weighing. In other words, each coin jumping from U to G gives us two points, and all other movements give us one points each.

The second hint is somewhat obvious. Whenever you’re facing a weighing that may only give you two results instead of the three (e. g. it’s impossible for the coins to balance out), you’re probably doing something wrong, unless it’s the last weighing.

The third hint is less obvious: if, at some point, you hit a decision tree branch that allows you to figure out the answer in less weighings than the given limit, you’re probably doing something wrong.

The last two hints are actually the two sides of the same coin, no pun intended: they both tell you that you’re going to create an unbalanced decision tree. In a well-balanced ternary tree most non-leaf nodes should have all three children, and the tree should ideally have the same height everywhere. Of course, that depends on the exact problem: if you’re allowed to do 100 weighings for 12 coins, you probably end up with lots of branches much shorter than that. But for three weighings it’s really desirable to balance everything out.

The last two hints are mostly redundant. If you’re squeezing as much information as possible, you would probably create a well-balanced tree anyway. So they just serve as additional warnings. But sometimes they simplify the math.

Back to the problem

So let’s try to build a good algorithm for 12 coins and 3 weighings. A 6/6 split is a bad idea because of the second hint. That’s how it simplifies the math, so we can instantly skip to an n/n split, where n<6. Since the situation is symmetrical for now, we don’t need to consider lighter/heavier results separately, so that leaves us two possible results of the weighing:

  1. The chosen coins balance out, therefore jumping right to G. The rest still belongs to U. That gives us 4n points (2n coins jumping from U to G).
  2. They don’t balance out. Therefore the lighter group goes to L, the heavier one to H and the rest straight to G because we know that the forged coin is among the weighed piles. That gives us 2n+2(12−2n) = 24−2n points.

The first expression increases with n, the second one decreases. If we find the point where they are equal, it’s obvious that the minimum will be less towards both directions from there: to the left 4n will be less, to the right 24−2n will be less. That gives us the following equation:

4n = 24−2n, 6n = 24, n = 4

Then we have two cases to consider.

Four coin piles balance out

The easiest case is when the coins balance out, so we now have just 4 U-coins. Intuitively, one may think of comparing two of them. If they balance out, we compare one of them with one of the remaining ones. If they balance out again, then the remaining one must be the forged one, but we don’t know whether it’s lighter or heavier. If the third weighing doesn’t balance out, then the third coin is the forged one (and we now know whether it’s lighter or heavier). If the second weighing doesn’t balance out, then we again compare one of them with one of the remaining ones, this time identifying not only which one is forged, but also whether it’s heavier or lighter. But there was still one case when we couldn’t do it. So let’s try to use our heuristics.

It makes no sense to compare good coins with good coins, so the only way we may end up putting good coins on the balance scale is to compare them with suspicious ones. This means that only one pan should contain good coins (if both of them do, we can just remove the minimum number of good coins from both pans). That means that we can have n1 U-coins on the left pan and n2 U-coins and n1-n2 G-coins on the right pan. Here, n2 can be zero (comparing suspicious coins with good ones), but then n1 can’t be 4 because all 4 U-coins can’t possibly balance out with 4 G-coins, and the second hint tells us it’s probably a bad thing. n1+n2 also can’t be 4 because of the same reason. So we have three cases now:

  1. Balancing out: 2(n1+n2) points for coins now promoted to G.
  2. The left side is lighter: n1+n2 points for promoting n1 coins to L and n2 coins to H. 2(4−n1−n2) points for promoting the rest to G.
  3. The left side is heavier: n1+n2 points for promoting n2 coins to L and n1 coins to H. 2(4−n1−n2) points for promoting the rest to G.

Note that even though cases 2 and 3 give equal number of points, the resulting group configuration is different if n1 ≠ n2. Now let n=n1+n2, then we have the following equation:

2n = 2(4-n), 3n = 8, n = 2 2/3

Let’s pick the closest integer value n = 3. Note that n1 and n2 by themselves don’t really matter, so let’s pick n1=3, n2=0. Going back to three cases:

  1. Balancing out: three coins are genuine, which means the remaining one is forged. We even have a spare weighing to determine if it’s lighter or heavier. Here is where 13 coins case breaks (the algorithm up to this point is the same): we can still determine which one of the remaining coins is forged, but with probability 1/2 we won’t know whether it’s lighter or heavier.
  2. Three U-coins are lighter: it means that the forged coin is among them and it’s lighter. Comparing any two of them will give us the answer.
  3. Three U-coins are heavier: the same as case 2, but the forged coin must be heavier.

See how using our heuristics allowed us to build a much simple algorithm than one may come up with intuitively, and how it’s also more powerful?

Four coins do not balance out

This case is much harder because we now have 4 L-coins, 4 H-coins and 4 G-coins which is a mess of possible combinations. Let’s pick n1 L-coins and m1 H-coins for the left pan, and n2 L-coins and m2 H-coins for the right pan, possibly adding some n1+m1−n2−m2 G-coins. Obviously we can’t use all L and H coins or else we can’t possibly balance out everything. The three cases now are:

  1. Balancing out: n1+m1+n2+m2 points for new G-coins.
  2. Pan 1 is lighter: m1+n2 points plus 8−n1−m1−n2−m2 points for not-participating coins. Where did m1+n2 points came from? Well, m1 coins were from H-group and now they are on the lighter side. The forged coin can’t possibly be both heavier and lighter, so it’s obviously then that these m1 coins are all genuine. Ditto with n2.
  3. Pan 1 is heavier: m2+n1+8−n1−m1−n2−m2. The same reasoning.

We now have three expressions and must do our best to balance them out. Let’s put it this way:

n1+m1+n2+m2=m1+n2+8−n1−m1−n2−m2

n1+m1+n2+m2=m2+n1+8−n1−m1−n2−m2

Subtracting one from another we get m1+n2=m2+n1. Let k denote this, that turns the first expression into 2k and the second and the third ones into 8-k. By solving 2k=8-k we get 3k = 8, much like in the previous case. And again, we have some freedom, but we can’t pick n1=3, m1=0, n2=3, m2=0, for example, because n1+n2=6 and we only have 4 L-coins. So let’s pick n1=3, m1=2, n2=1, m2=0. We’ll also need to add all 4 genuine coins to the right pan.

  1. Balancing out: we’re now left with 2 H-coins. Finding out which one is forged is a piece of cake.
  2. The left pan is lighter: we’re left with 3 L-coins. The right pan did not contain any H-coins, so it’s obviously that the forged one is among those 3. Again, it’s trivial to solve.
  3. The left pan is heavier: we’re left with 2 H-coins from the left side an 1 L-coin from the right side. Comparing the two H-coins we will instantly know which one of them is heavier and therefore is the forged one, in case they don’t balance out. If they do, then the forged one must be the remaining L-coin.

Problem solved! We didn’t even have to try different variations (but you can, and you’ll get correct algorithms). And we also didn’t have to use the third hint.

Encodings, Unicode and broken code

This is another sad tale of character encodings. Consider this LeetCode problem that asks to check whether the given strings are isomorphic. Isomorphic strings being defined as strings of the same length with a bijection mapping between the characters. For example, “aba” is isomorphic to “ava” with mapping a \leftrightarrow a, b \leftrightarrow v and “mlm” with mapping a \leftrightarrow m, b \leftrightarrow l, but not to “aaa” (no bijection since both “a” and “b” are mapped to “a”).

Now consider possible solutions in Java. One obvious solution:

Runs in 36 ms, certainly not the fastest submission. One way to “optimize” it:

This runs in 12 ms. Three times faster! Beating 92%! And here is yet another version:

Now, let me ask a question: which of the solutions above is the best one?

The last one is something an English speaker with C background might come up with. It will obviously break for any characters outside US-ASCII, including Cyrillic, Chinese, Hebrew or even German or Irish (because of the umlauts and fada). So obviously it’s not acceptable.

The second one is trickier. One thing is that it might break if one of the strings contains NUL characters because we abuse NUL as the “character not mapped” special value. Another thing is that initializing the whole array with zeroes takes \mathcal{O}(65536) time which could make it a poor choice for short strings.

So it looks like the first one is the best, right? It scales nice to any lengths, and even though it’s slower, it handles NULs properly.

Well, the answer is: all of them are wrong! One test case that none of the solutions above will pass is “ab”, “冬b”. In case you can’t see it, here is a picture:

kanji

That’s right, that one weird Chinese character is enough to break all of the solutions above. Moreover, it breaks LeetCode testing system as well (just like Cyrillic or anything non-ASCII does) and LeetCode Discuss forums too (unlike Cyrillic and many other non-ASCII symbols). Why? What’s wrong with that particular character? Java stores strings using Unicode, right? That’s why char is two bytes, after all! So it should be able to handle any characters without any problems! The dark age of terrible national encodings is over!

In order to understand it, we must look back at the history of encodings and Uncode.

It all started in 1960s or even long before that (Morse code came into existence long before the first computer). But it’s in 1960s that all hell broke loose. In 1963 both ASCII and EBCDIC were introduced. While even EBCDIC is apparently still in use today, it’s ASCII that became widespread, and the fact that ASCII was a 7-bit encoding meant that there was one “free” bit and 128 unused codes in the 128-255 range. That, and the lack of any letters except basic Latin, immediately gave birth to a myriad of various national encodings. Worse, multiple encodings were sometimes used for the same languages. I know of four Russian, for example: code page 866 (“MS-DOS” encoding), code page 1251 (”Windows” or ANSI encoding), KOI8-R (a really weird encoding that arranges letter according to English alphabet, not Russian one, was really widespread in the early days of Russian Internet) and the “standard” ISO-8859-5 that was rarely used at all. This is still a major source of various troubles, as when you run a program in a console window, you have no idea which encoding will be used and therefore you have about 50% chance of getting garbage (less in practice because most programs will use the MS-DOS encoding). And nobody plans to fix it because it is impossible and because nobody cares about console windows nowadays.

Chinese and Japanese people got it even worse: 128 values are obviously not enough to represent about 2000 ideographs in Japanese (and that’s only a subset of Chinese!), so they went ahead and invented two-byte encodings, which made things much worse because now, having some bytes, you couldn’t even determine the string length if you had no idea which encoding is used.

Then Unicode came into being. The first standard was published in 1991 and it introduced a 16-bit encoding intended for universal use, which included all characters deemed reasonable. Unfortunately, the bunch of Old Evil Encodings didn’t disappear at the very same moment, so the only thing that really happened that day is that the world now had one more encoding to deal with. No, wait, make it two encodings because Unicode defined characters as 16-bit units, but those can be represented with bytes using either Little Endian or Big Endian order.

Even worse, Unicode apparently failed to consider some important characters like rarely used ideographs (like that 冬), even though they are a part of personal names and names of places. Imagine you can’t type your own name as you’re trying to use some software! So apparently some extension was needed. That is how Unicode transformed from a single 16-bit encoding into a whole standard of concepts and encodings.

The core concept is the code point. A code point is a 21-bit number corresponding to some character, typically represented as a 32-bit integer in memory and as something like U+00B0 in writing, where 00B0 is the hexadecimal of the code point (in this case it’s the degree sign: °). The current range for the code points is U+0000–U+10FFFF, hence 21 bit (but it’s extendable). So, you see, to say that Unicode is a 16-bit encoding is wrong in several ways: Unicode is a standard (defining multiple encodings), not an encoding, and not all Unicode encodings are 16-bit.

The code points defined in the first Unicode standard now belong to the so-called Basic Multilingual Plane (BMP), and that includes code points in the range U+0000–U+FFFF. That is Latin, English, Arabic, Hebrew, most Chinese and Japanese and lots of other useful things. However, there are some Chinese symbols outside the BMP, which belong to the so-called Supplementary Plane, and the code points U+10000 and above are called supplementary code points (or characters).

There are three main encodings in the current Unicode standard. By “main” I mean that they are both part of the standard and are widely used. These are:

  1. UTF-8, which is a variable width character encoding, where a code point can be represented by one to four bytes (to six bytes if we ever need code points above U+200000). Good thing about it is that NUL byte is only used to represent the NUL code point, so UTF-8 strings can be NUL-terminated. Another good thing is that ASCII characters are represented by single bytes identical to their ASCII representation.
  2. UTF-16, which is also (surprise!) a variable width character encoding, where a code point can be represented by one or two 16-bit code units (which, in turn, can be represented by two bytes using either BE or LE byte order, that makes UTF-16LE and UTF-16BE). BMP code points are represented by one code unit, supplementary code points are represented by the so-called surrogate pairs, which consist of the first (high) surrogate and the second (low) surrogate. The high/low concept doesn’t really have anything to do with byte ordering here, they encode higher and lower bits of the code point, and the high surrogate always comes first regardless of the byte order.
  3. UTF-32 is a fixed width character encoding where each code point is encoded as a single 32-bit number (which, again, makes it UTF-32LE or UTF-32BE depending on the byte order).

As you can see, UTF-16 is pretty messed up, and if you consider it a fixed-width character encoding, you may end up in trouble. In fact, when I finally figured out all this, I started to think that UTF-16 is outright evil: it doesn’t have the nice properties of UTF-8 (like NUL-termination and ASCII compatibility) and its only advantage over UTF-32 is lower memory consumption, but with modern amounts of RAM it shouldn’t be a real problem any more. And the fact that it’s a variable width encoding screwes up almost any text processing algorithm you can think of. Here is a correct solution for the mentioned LeetCode problem, for example.

It’s certainly not as efficient as the others, but it’s the one that really works (and no, you can’t say it works unless it handles all possible inputs correctly). Some useful String and Character methods include:

  • String.codePointCount: returns the number of code points between the specified indexes. This is the true length of the string (not the number returned by String.length).
  • String.offsetByCodePoints: “adds” two indexes together, when one index is a char index and another one is measured in code points, returning the resulting char index. For example, if you have the string “冬b”, then offsetByCodePoints(0, 1) would return 2 because “b” is located at index 2, not 1. A call to offsetByCodePoints(2, 1) would return 3 (the end of the string) because “b” is only a single code unit. This method is kind of reversed version of the previous one.
  • CharSequence.codePoints: returns an IntStream of code points.
  • Character.codePointAt, Character.codePointCount: same as the String method, only for character arrays.
  • Character.highSurrogate, Character.lowSurrogate: return the respective surrogate for a given code point.
  • Character.isHighSurrogate, Character.isLowSurrogate: for a given code unit, check whether it’s a part of a possible surrogate pair. This is very important method for many cases when you need to be able to distinguish surrogate pairs from BMP characters. For example, StringBuilder.reverse uses it to properly reverse a string contains surrogates (because they obviously don’t need to be reversed).

On top of that, many methods have two variants: one accepting a char, other accepting a code point. Those accepting chars should really be deprecated because they actually encourage writing buggy code.

Considering all that, we must conclude that while Unicode indeed made life much easier than it was in the Dark Ages, it must be handled properly unless we want to enter another dark age where a person may fail to register an account on some site simply because he happened to have a supplementary character. Or wait a minute. We have already entered it. Now we must get out, so we all better start writing bug-free code!