Hacking the IntegerCache in Java 9

Five years ago I published an article in Hungarian about how to alter the IntegerCahe in the JDK. Doing that is essentially hacking the Java run-time and there is no practical advantage unless while you develop the hacking code you get a better understanding how reflection works and how the Integer class is implemented.

The Integer class has a private nested class named IntegerCache that contains Integer objects for the int values -127 to 128. When the code has to box an int to Integer and the value is within this range then the run-time uses the cache instead of creating new Integer object. This is done for speed optimization reasons bearing in mind that the int values in programs are many times in this range (think about array indexing).

The side effect of this is that many times using the identity operator to compare two Integer objects may work so long as long the value is in the range. This is typically during unit test. In operational mode, when some of the values get bigger than 128 the code fails.

Hacking the IntegerCache using reflection may also lead to mysterious side effects and note that this is something that has its effect on the whole JVM. If a servlet redefines the small Integer cached values then all other servlets running in the same Tomcat under the same JVM will suffer.

There are other articles about it on the net from Lukas Eder

Add Some Entropy to Your JVM

and on the excellent blog site Sitepoint:


Now that I started to play around with Java 9 early access version it came to my mind if I can do the same hacking with the new version of Java. Before starting that let’s refresh what we did with Java 8.

Lukas in his article displays a sample code, I copy here:

import java.lang.reflect.Field;
import java.util.Random;
public class Entropy {
  public static void main(String[] args) 
  throws Exception {
    // Extract the IntegerCache through reflection
    Class<?> clazz = Class.forName(
    Field field = clazz.getDeclaredField("cache");
    Integer[] cache = (Integer[]) field.get(clazz);
    // Rewrite the Integer cache
    for (int i = 0; i < cache.length; i++) {
      cache[i] = new Integer(
        new Random().nextInt(cache.length));
    // Prove randomness
    for (int i = 0; i < 10; i++) {
      System.out.println((Integer) i);

The code gets access to the IntegerCache via reflection and then fills the cache with random values. Naughty.

We can try to execute the same code in Java 9. Do not expect much fun though. Java 9 is more serious when somebody tries to violate it.

Exception in thread "main" java.lang.reflect.InaccessibleObjectException:
  Unable to make field static final java.lang.Integer[]
  accessible: module java.base does not "opens java.lang" to unnamed module @1bc6a36e

We get an exception that did not exist in Java 8. It says that object is not accessible because the module java.base, which is the part of the run-time of the JDK that is automatically imported by each Java program does not ‘opens’ (sic) the module to the unnamed module. It is thrown from the line where we try to set the field accessible.

The object we could easily access in Java 8 is not accessible any more, because the module system protects it. A code can only access fields, methods, and other things using reflection only if the class is in the same module, or if the module opens the package for reflective access for the world or for the module that needs the access. This is done in the module-info.java module definition file, like

module myModule {
    exports com.javax0.module.demo;
    opens com.javax0.module.demo;

The module java.base does not open itself for reflective access for us and especially not for the unnamed module, which is the code that we run. If we create a module for our code and name it then the error message will contain the name of that module.

Can we open the module programmatically? There is an addOpens method in the java.lang.reflect.Module module. Will it work?

Bad news for the hackers that it will not. It can only open a package in a module to another module if that package is already opened for the module calling this method. That way modules can pass on to other modules the right that they already have to access some packages in a reflective way but can not open things that are not open.

But the same time it is a good news. Java 9 is not so easily hackable like Java 8 was. At least this little hole is closed. It seems that Java starts to be professional grade and not to be a toy. Soon the time will come when we can migrate serious programs from RPG and COBOL to Java. (Sorry for the joke.)


After the article was republished on DZONE Peter Runge pointed out that the module system in this case still can be neglected using sun.misc.Unsafe class. Based on his suggestion the whole hack is here:

public class IntegerHack {

    public static void main(String[] args)
            throws Exception {
        // Extract the IntegerCache through reflection
        Class usf = Class.forName("sun.misc.Unsafe");
        Field unsafeField = usf.getDeclaredField("theUnsafe");
        sun.misc.Unsafe unsafe = (sun.misc.Unsafe)unsafeField.get(null);
        Class<?> clazz = Class.forName("java.lang.Integer$IntegerCache");
        Field field = clazz.getDeclaredField("cache");
        Integer[] cache = (Integer[])unsafe.getObject(unsafe.staticFieldBase(field), unsafe.staticFieldOffset(field));
        // Rewrite the Integer cache
        for (int i = 0; i < cache.length; i++) {
            cache[i] = new Integer(
                    new Random().nextInt(cache.length));

        // Prove randomness
        for (int i = 0; i < 10; i++) {
            System.out.println((Integer) i);

How object initialization works

You may got used to my habit writing about something special, non trivial Java feature or usage. This time it will be a little different. At least for the start. This is a video tutorial about object initialization. We have an interface. Then we have an abstract class that implements the interface and then a concrete class that extends the abstract class. They do nothing except writing some strings to the console when they are executed so we can see what order they are executed. They have static initializer blocks, wherever it possible, non static initializer blocks and constructors.

BTW: can you tell, and be honest to yourself: is it allowed to have a static initializer block inside an interface? If you know java very well, but you can not answer that question with absolute certainty it will not hurt to watch this 9 minute tutorial.

And also stay tuned for the second part, when we get back to real javax0 style and let the hell loose.

While you wait for the second tutorial here is a puzzle:

How is it possible to have an instance of the Concrete class even though calling new Concrete() throws
Exception in thread "main" java.lang.NoClassDefFoundError: Could not initialize class com.javax0.classinit.Concrete

If you could or could not find the answer to the puzzle watch the second part of the tutorial:

The source code is available from https://github.com/javax0-tutorials/object-initialization.

Java 9 by Example, My New Book

Sometime during the summer, I decided to write a book on Java programming after being suggested to do so by Packt. Java is a market leader and the number one programming language in the enterprise programming arena, and learning it is a good option for novice programmers. I recommend it to be learned as a main language after you got your fingers burnt with languages that have a simpler ecosystem, such as Python, Delphy, VisualBasic, and so on. Many advocate the death of Java but I do not share their opinion. There may be more modern and fancier languages, but for enterprise computing Java is still there and will be there, at least for the next 20 years. If you learn Java now, you learn an actively developing, stable, and reliable environment and tool, and you gain significant knowledge that you can convert to “jobs” in the coming decades.

An overview of the book

While designing the book, I decided to address those readers who already have some programming experience and want to learn Java as a main language, but apart from that, the book starts with the basics. Java 9 is especially good to get started since it has a REPL interpreter that compiles the Java code you type in, so you can try the features interactively. Throughout the book, you will see sample programs, first simple ones and then more complex examples, that are explained in detail. We focus not only on the language features, such as module support, functional programming, lambda expressions, and reactive interfaces, but also on programming style and program design. Continuously tutoring and coaching junior developers in my everyday work, I have gathered some experience on what is important and yet easily overlooked by beginners, and I have focused on these issues in the book.

The examples include sorting algorithms, explaining bubble and quick short, a game called Mastermind, a sample e-Commerce application, and a simple accounting application. The game, Mastermind, is followed in three chapters: the basic algorithm, a massively parallel algorithm (which is not trivial for this problem), and a web application where you can finally see the colors on the screen.

Finishing the book, the reader will have a comprehensive view of the language and will gain a stable basic knowledge to study further in the special directions he or she chooses.

Java 9 by Example Book Cover

How to get the book

This book is currently work in progress at the moment. You can however get an early access eBook from the Packt Website at https://www.packtpub.com/application-development/java-9-programming-example. Here you can see pre-reviewed drafts of the chapters as they are written, giving you access to content as early as possible. To know more about Early Access click on the below link. https://www.packtpub.com/books/info/packt/early-access

Final volatile

I was writing my book over the weekend and I was looking for some simple example that could demonstrate the real need of volatile modifier in multi-thread code. Years ago when I last time demonstrated the multi-thread capability Java was still 32-bit, or at least there was 32-bit Java available. On 32 bits you could concurrently increment long variables and because the lower and upper 32 bits were handled in different processor shift there was a chance that two threads garbled some way the non-volatile variable. Now with Java 9 this is not the case. Now Java is 64-bit and I had to demonstrate the need for a volatile on 64-bit before anyone comes up the stupid idea that it was only needed for 32-bit. (I could tell stories, but I try to keep it a professional blog. Not with much success, but still.)

I was searching stackoverflow and found this page that contains many meaningless, or less than usable answer (which clearly demonstrates that the topic is not simple) but it also contains a sample from Jed Wesley-Smith that inspired my demonstrating code for the book:

package packt.java9.by.example.thread;

public class VolatileDemonstration implements Runnable {
    private Object o = null;
    private static final Object NON_NULL = new Object();
    public void run() {
        while( o == null );
        System.out.println("o is not null");
    public static void main(String[] args)
                           throws InterruptedException {
        VolatileDemonstration me = new VolatileDemonstration();
        new Thread(me).start();
        me.o = NON_NULL;

This code will never finish, unless you convert the field o volatile. We also need the 1000ms sleep to allow the JIT to optimize the code of the method run() after which it never reads the variable o ever again. The JIT assumes intra-thread semantics and takes the liberty to optimize the code that way. (Java Language Specification 17.4.7)

But what happens if you have a field that you can not convert to volatile? What? Can’t you just write the keyword volatile in front of the type Object? Perhaps I was giving too much hint in the title of the article…

A final field can not be volatile. Of course: a final can not change, there is no point to re-read it from the main memory and waste CPU cycles for the synchronization of any change of it between the CPU caches. But that is not true.

Final variables can be changed once.

This is something that novice Java developers tend to forget. When an object is created any final field has the zero value. In case of an object this value is null. The field has to get its final value until the end of the initialization process, that is until the end of the execution of the constructor (any constructor). Look at the following code:

package packt.java9.by.example.thread;

public class VolatileDemonstration implements Runnable {
    private final Object o;
    private static final Object NON_NULL = new Object();
    public void run() {
        while( o == null );
        System.out.println("o is not null");

    public VolatileDemonstration() throws InterruptedException {
        new Thread(this).start();
        this.o = NON_NULL;

The constructor starts the new thread, sleeps and then sets the field that can not be volatile. What is the solution?

What solution? There is no solution! This is a demonstration code. Just don’t write code that does things like this: that is the solution. OK?


What can we learn from this? Not all of the followings can be directly implied from the above, but they are all related to the phenomenon. I could write a longer article leading to any of the followings but it would have only abused your patience.


  • Final fields can be changed once. It is not true that they are not changing never (sic).
  • A thread may read the value of a final field once and it may not read it ever again. If the JVM runs for years the thread may keep the value in the thread context in some registry or CPU cache for years as long as it likes.
  • Never let this escape from the constructor.
  • Among other more trivial things the “never let this escape from the constructor” also means not to pass it as argument to a method that can be overridden or not under the control of the programmer, who is responsible for the current class.
  • Write well behaving code or else you will suffer the slings and arrows of your outrageous program.


  • See the takeaways for juniors and teach them.
  • You have a nice brain twister code for education.
  • Java is not a perfect language allowing such constructs. But do not tell juniors. When they realize it they are already seniors and then it is just too late.
  • The solution is a liquid mixture in which the minor component is uniformly distributed within the major component.

Microbenchmarking comes to Java 9

I have not written article here for a few months and this will also continue with this exception. I plan to return writing around next year March. Explanation at the end of the this article. Wait! Not exactly at the end, because you could just scroll down. It is somewhere towards the end of the article. Just read on!

Three years ago I was writing about how Java compiler optimizes the code it executes. Or rather how javac does not do that and the same time JIT does. I made some benchmarks, some really bad ones as it was mentioned by Esko Luontola. These benchmarks were meant to show that JIT optimize even before it could gather significant statistical data about the execution of the code.

The article was created in January 2013. and the very first source code upload of JMH (Java Microbenchmark Harness) happened two month later. Since that time the harness developed a lot and next year it becomes part of the next release of Java. I have a contract to write a book about Java 9, and its chapter 5 should cover Java 9 microbenchmarking possibilities, among other things. It is a good reason to start something to play with around JMH.

Before getting into the details how to use JMH and what it is good for, let’s talk about a bit microbenchmarking.


Microbenchmarking is measuring the performance of some small code fragment. It is rarely used and before starting to do a microbenchmark for real commercial environment we have to think twice. Remember that premature optimization is root of all evil. Some developers created a generalization of this statement saying that optimization itself is root of all evil, which may be true. Especially if we mean microbenchmarking.

Microbenchmarking is a luring tool to optimize something small without knowing if it is worth optimizing that code. When we have a huge application that has several modules, run on several servers how can we be sure that improving some special part of the application drastically improves the performance? Will it pay back in increased revenue that generates so much profit that will cover the cost we burnt into the performance testing and development? I am reluctant to say that you can not know that but only because such a statement would be too broad. Stadistically almost sure that such an optimization including microbenchmarking will not pain off most of the time. It will hurt, you just may not notice it, or even enjoy it, but that is a totally different story.

When to use microbenchmarking? I can see three areas:

  1. You write an article about microbenchmarking.
  2. You identified the code segment that eats most of the resources in your application and the improvement can be tested by microbenchmarks.
  3. You can not identify the code segment that will eat most of the resources in an application but you suspect it.

The first area is a joke. Or not: you can play around with microbenchmarking to understand how it works and then to understand how Java code works, what runs fast and what does not. Last year Takipi posted an article where they tried to measure the speed of lambdas. Read it, very good article and clearly demonstrates the major advantage of blogging over writing something for the print. Readers commented and pointed out errors and they were corrected in the article.

The second is the usual case. Okay, before a reader, commented corrects me: the second should have been the usual case. The third is when you develop a library and you just do not know all the applications that will use it. In that case you will try to optimize the part that you think is the most crucial for most of the imagined, suspected applications. Even in that case it is better to take some sample applications.


What are the pitfalls of Microbenchmarking? Benchmarking is done as experiment. The first programs I wrote were TI calculator code and I could just count the number of steps the program made to factor two large (10 digits that time) prime numbers. Even that time I was using an old Russian stop watch to measure the time being lazy to calculate the number of steps. Experiment and measurement was easier.

Today you could not calculate the number of steps the CPU makes. There are so many small factors that may change the performance of the application that are out of control of the programmer that it is impossible to make a calculation of the steps. We have the measurement left for us and we gain all the problems with all the measurements.

What is the biggest problem of measurements? We are interested in something, say X and we usually can not measure that. So we measure instead Y and hope that the value of Y and X are coupled together. We want to measure the length of the room, but instead we measure the time it takes for the laser beam to travel from one end to the other. In this case the length X and the time Y are strongly coupled. Many times X and Y only correlate more or less. Most of the times when people do measurement the values X and Y have no relation to each other at all. Still people put their money and more on decisions backed by such measurements. Think about the political elections as an example.

Microbenchmarking is no different. It is hardly ever done well. If you are interested in details and possible pitfalls Aleksey Shipilev has a good one hour video. The first question is how to measure the execution time. Small code runs short times and System.currentTimeMillis() may just return the same value when the measurement starts and when it ends, because we are still in the same millisecond. Even if the execution is 10ms the error of the measurement is still at least 10% purely because of the quantization of the time as we measure. Luckily there is System.nanoTime(). We happy, Vincent?

Not really. nanoTime() returns the current value of the running Java Virtual Machine’s high-resolution time source, in nanoseconds as the documentation says. What is “current”? When the invocation was made? Or when it was returned? Or sometime between? Select the one you want and you may still fail. That current value could have been the same during the last 1000ns that is all Java implementations should guarantee.

And another caveat before using nanoTime() from the documentation: Differences in successive calls that span greater than approximately 292 years (263 nanoseconds) will not correctly compute elapsed time due to numerical overflow.

292 years? Really?

There are other problems as well. When you start up a Java code the first few thousand executions of the code will be interpreted or executed without run-time optimization. JIT has the advantage over compilers of statically compiled languages like Swift, C, C++ or Golang that it can gather run-time information from the execution of the code and when it sees that the compilation it performed last time could have been better based on recent run-time statistics it compiles the code again. The same may be true for the garbage collection that also tries to use statistics to tune its operational parameters. Because of this well written server applications gain a bit of performance over time. They start up a bit slower and then they just become faster. If you restart the server the whole iteration starts again.

If you do micro benchmarks you should care about this behavior. Do you want to measure the performance of the application during warm-up time or how it really executes during operation?

The solution is a micro benchmarking harness that tries to consider all these caveats. The one that gets to Java 9 is JMH.

What is JMH?

“JMH is a Java harness for building, running, and analyzing nano/micro/milli/macro benchmarks written in Java and other languages targeting the JVM.” (quote from the official site of JMH)

You can run jmh as a separate project independent from the actual project you measure or you can just store the measurement code in a separate directory. The harness will compile against the production class files and will execute the benchmark. The easiest way, as I see, is to use the Gradle plugin to execute JMH. You store the benchmark code in a directory called jmh (the same level as main and test) and create a main that can start the benchmark.

import org.openjdk.jmh.annotations.*;
import org.openjdk.jmh.runner.Runner;
import org.openjdk.jmh.runner.RunnerException;
import org.openjdk.jmh.runner.options.Options;
import org.openjdk.jmh.runner.options.OptionsBuilder;
import java.io.IOException;

public class MicroBenchmark {

public static void main(String... args) throws IOException, RunnerException {
Options opt = new OptionsBuilder()

new Runner(opt).run();

There is a nice builder interface for the configuration and a Runner class that can execute the benchmarks.

Playing a bit

In the book Java 9 Programming By Example one of the examples is the Mastermind game. Chapter 5 is all about solving the game parallel to speed up the guessing. (If you do not know the game, please read it on Wikipedia, I do not want to explain it here, but you will need it to understand the following.)

The normal guessing is simple. There is a secret hidden. The secret is four pegs of four different color out of 6 colors. When we guess we take the possible color variations one after the other and ask the question the table: if this selection is the secret are all answers correct? In other words: can this guess be hidden or is there some contradiction in the answers for some previous answers? If this guess can be the secret then we will give it a try putting the pegs on the table. The answer may be 4/0 (alleluia) or something else. In the latter case we go on searching. This way the 6 color, 4 columns table can be solved in five steps.

For the sake of simplicity and visualization we name the colors with numbers, like 01234456789 (we have ten colors in the jmh benchmark since 6 colors are just no enough) and 6 pegs. The secret we use is 987654 because this is the last guess as we go from 123456, 123457 and so on.

When I first coded this game in August 1983 on a Swedish school computer (ABC80) in BASIC language each guessing took 20 to 30 seconds on the z80 processor running on 40MHz 6 colors, 4 positions. Today my MacBook Pro can play the whole game using single thread approximately 7 times in a second using 10 colors and 6 pegs. But that is not enough when I have 4 processors in the machine supporting 8 parallel threads.

To speed up the execution I split up the guess space into equal intervals and I started separate guessers each spitting guesses into a blocking queue. The main thread reads from the queue and puts the guesses on the table as they come. There are some post processing that may be needed in case some of the threads create a guess that becomes outdated by the time the main thread tries to use it as a guess but still we expect huge speed up.

Does it really speed up the guessing? That is JMH here for.

To run the benchmark we need some code that actually executes the game

public static class ThreadsAndQueueSizes {
@Param(value = {"1", "4", "8", "16", "32"})
String nrThreads;
@Param(value = { "1", "10", "100", "1000000"})
String queueSize;


public void playParallel(ThreadsAndQueueSizes t3qs) throws InterruptedException {
int nrThreads = Integer.valueOf(t3qs.nrThreads);
int queueSize = Integer.valueOf(t3qs.queueSize);
new ParallelGamePlayer(nrThreads, queueSize).play();

public void playSimple(){
new SimpleGamePlayer().play();

The JMH framework will execute the code several time measuring the time to run with several parameters. The method playParallel will be executed to run the algorithm for 1, 4, 5, 10 and 32 threads each with 1, 10, 100 and one million maximum queue length. When the queue is full the individual guessers stop with their guessing until the main thread pulls at least one guess off the queue.

I suspected if we have many threads and we do not limit the length of the queue then the worker threads will fill the queue with initial guesses that are just based on an empty table and thus does not deliver much value. What do we see after almost 15 minutes of execution?

Benchmark                    (nrThreads)  (queueSize)   Mode  Cnt   Score   Error  Units
MicroBenchmark.playParallel            1            1  thrpt   20   6.871 ± 0.720  ops/s
MicroBenchmark.playParallel            1           10  thrpt   20   7.481 ± 0.463  ops/s
MicroBenchmark.playParallel            1          100  thrpt   20   7.491 ± 0.577  ops/s
MicroBenchmark.playParallel            1      1000000  thrpt   20   7.667 ± 0.110  ops/s
MicroBenchmark.playParallel            4            1  thrpt   20  13.786 ± 0.260  ops/s
MicroBenchmark.playParallel            4           10  thrpt   20  13.407 ± 0.517  ops/s
MicroBenchmark.playParallel            4          100  thrpt   20  13.251 ± 0.296  ops/s
MicroBenchmark.playParallel            4      1000000  thrpt   20  11.829 ± 0.232  ops/s
MicroBenchmark.playParallel            8            1  thrpt   20  14.030 ± 0.252  ops/s
MicroBenchmark.playParallel            8           10  thrpt   20  13.565 ± 0.345  ops/s
MicroBenchmark.playParallel            8          100  thrpt   20  12.944 ± 0.265  ops/s
MicroBenchmark.playParallel            8      1000000  thrpt   20  10.870 ± 0.388  ops/s
MicroBenchmark.playParallel           16            1  thrpt   20  16.698 ± 0.364  ops/s
MicroBenchmark.playParallel           16           10  thrpt   20  16.726 ± 0.288  ops/s
MicroBenchmark.playParallel           16          100  thrpt   20  16.662 ± 0.202  ops/s
MicroBenchmark.playParallel           16      1000000  thrpt   20  10.139 ± 0.783  ops/s
MicroBenchmark.playParallel           32            1  thrpt   20  16.109 ± 0.472  ops/s
MicroBenchmark.playParallel           32           10  thrpt   20  16.598 ± 0.415  ops/s
MicroBenchmark.playParallel           32          100  thrpt   20  15.883 ± 0.454  ops/s
MicroBenchmark.playParallel           32      1000000  thrpt   20   6.103 ± 0.867  ops/s
MicroBenchmark.playSimple            N/A          N/A  thrpt   20   6.354 ± 0.200  ops/s

(In score the more is the better.) It shows that the best performance we get if we start 16 threads and if we somewhat limit the length of the queue. Running the parallel algorithm on one thread (a mater and a worker) is somewhat slower than the single thread implementation. This seems to be okay: we have the overhead of starting a new thread and communication between the threads. The maximum performance we have is around 16 threads. Since we can have 8 cores in this machine we expected the peek around 8. Why is that?

What happens if we replace the standard secret 987654 (which is boring after a while even for a CPU) with something random?

Benchmark                    (nrThreads)  (queueSize)   Mode  Cnt   Score   Error  Units
MicroBenchmark.playParallel            1            1  thrpt   20  12.141 ± 1.385  ops/s
MicroBenchmark.playParallel            1           10  thrpt   20  12.522 ± 1.496  ops/s
MicroBenchmark.playParallel            1          100  thrpt   20  12.516 ± 1.712  ops/s
MicroBenchmark.playParallel            1      1000000  thrpt   20  11.930 ± 1.188  ops/s
MicroBenchmark.playParallel            4            1  thrpt   20  19.412 ± 0.877  ops/s
MicroBenchmark.playParallel            4           10  thrpt   20  17.989 ± 1.248  ops/s
MicroBenchmark.playParallel            4          100  thrpt   20  16.826 ± 1.703  ops/s
MicroBenchmark.playParallel            4      1000000  thrpt   20  15.814 ± 0.697  ops/s
MicroBenchmark.playParallel            8            1  thrpt   20  19.733 ± 0.687  ops/s
MicroBenchmark.playParallel            8           10  thrpt   20  19.356 ± 1.004  ops/s
MicroBenchmark.playParallel            8          100  thrpt   20  19.571 ± 0.542  ops/s
MicroBenchmark.playParallel            8      1000000  thrpt   20  12.640 ± 0.694  ops/s
MicroBenchmark.playParallel           16            1  thrpt   20  16.527 ± 0.372  ops/s
MicroBenchmark.playParallel           16           10  thrpt   20  19.021 ± 0.475  ops/s
MicroBenchmark.playParallel           16          100  thrpt   20  18.465 ± 0.504  ops/s
MicroBenchmark.playParallel           16      1000000  thrpt   20  10.220 ± 1.043  ops/s
MicroBenchmark.playParallel           32            1  thrpt   20  17.816 ± 0.468  ops/s
MicroBenchmark.playParallel           32           10  thrpt   20  17.555 ± 0.465  ops/s
MicroBenchmark.playParallel           32          100  thrpt   20  17.236 ± 0.605  ops/s
MicroBenchmark.playParallel           32      1000000  thrpt   20   6.861 ± 1.017  ops/s

The performance increases since we do not need to go though all the possible variations. In case of one thread the increase is double. In case of multiple threads the gain is not that much. And note that this does not speed the code itself up, only measures more realistically using statistical, random secrets. What we can also see that the gain of 16 threads over 8 threads is not significant any more. This is significant only when we select a secret that is towards the end of the variations. Why? From what you have seen here and from the source code available in GitHub you can give an answer to that.


The book Java 9 Programming By Example is planned to be released February 2017. But since we are living in an open source world you can get access controlled by the publisher to 1.x.x-SNAPSHOT versions. Now I told you the preliminary GitHub URL that I use while I develop code for the book and you can also preorder the eBook and give feedback helping me to create a better book.

Try and Catch in Golang

Golang as opposed to Java does not have exceptions, try/catch/finally blocks. It has strict error handling, functions called panic and recover and a statement named defer. It is a totally different approach. Is it better or is the Java approach the superior? (Sorry that I keep comparing it to Java. I am coming from Java world.)

When we handle exceptional cases in Java we enclose the commands into a ‘try’ block denoting that something may happen that we want to handle later in a ‘catch’ block. Then we have the ‘finally’ block that contains all the things that are to be executed no matter what. The problem with this approach is that it separates the commands that belong to the same concern. We want to deal with some file. So we open a file and later, no matter what, we want to close it. When the programmer writes the finally block the file opening is far away somewhere at the start of the method. To remember all the things that we have to do to clean up the actions at the start of the method you have to scroll up to the start of the method where the ‘try’ block starts.

Okay! I know that your method is too long if you have to scroll back. Your methods follow clean code principles and are not longer than ten lines each including JavaDoc. Even though the issue is still there. It is formulated according to order the execution is expected and not according to the order the logic dictates. The logic says the following: if I open a file, I will want to close it. If I allocate some resource I will want to release it. It is better keeping the concerns together. We are not programing in assembly where you write the mnemonics in the strict order of execution. We define the algorithmic solution in a high level language and the compiler will generate the assembly. Real work has to be done by the brain, mechanical work is for the CPU. These days we have CPUs.

Golang has the command ‘defer’ for the purpose. You open a file and you mention on the next line that you will want it to be closed some time calling the function you provide. This is the much better approach, which the developers of the Java language also know hence introducing the interface ‘closeable’ and try-with-resources statement.

Still programmers coming from the Java world begin introduced to Go are longing for exception handling. If you really want you can mimic it in Go. It will not be the same and I do not really get the point why to ruin something that is good to something old and mediocre, but you can write

		Try: func() {
			fmt.Println("I tried")
		Catch: func(e Exception) {
			fmt.Printf("Caught %v\n", e)
		Finally: func() {

Homework: find out the sample code that is before these lines (Go constructs) that make this possible. Solution is here: https://play.golang.org/p/LXroobH8SM

package main

import (

type Block struct {
	Try     func()
	Catch   func(Exception)
	Finally func()

type Exception interface{}

func Throw(up Exception) {

func (tcf Block) Do() {
	if tcf.Finally != nil {

		defer tcf.Finally()
	if tcf.Catch != nil {
		defer func() {
			if r := recover(); r != nil {

func main() {
	fmt.Println("We started")
		Try: func() {
			fmt.Println("I tried")
		Catch: func(e Exception) {
			fmt.Printf("Caught %v\n", e)
		Finally: func() {
	fmt.Println("We went on")

See also a recent similar solution at http://hackthology.com/exceptions-for-go-as-a-library.html from Tim Henderson

Do not (only) meet the budget

In a previous article I wrote

The actual decision (of a software architect) should lead to a solution that meets availability, performance, reliability, scalability, manageability and cost criteria. (Btw: the first six criteria should be met, the last one should be at least met and minimized, but that is a different story.)

Many times the criteria are met and there is no intention to minimize the cost. “There is a budget and we have to fit into it.” This is the approach teams follow. There are several reasons for it. But the reasons do not necessarily mean that the approach is ok. I may even accept the argument that this behaviour is unavoidable in large organizations.

Why is this approach bad?

When you sell something you want to sell it the highest price you can. Cost represents a minimum for the selling price: if the reachable price is lower than the cost to reproduce then production will stop. Budget is also a limiting factor. You go to the food shop and you buy the bread that meets your likes and is the cheapest among those if you have the money. If your money is limited you will select one that you can pay for. Why would one buy the more expensive if all other criteria they need are met?

(Do not start to talk about Apple products: feeling you are rich is also a need.)

The same is true for development projects even if the customer buying the development is in the same company. Your customer is either “business” if you are an in-house team or sales in case your company develops software for customes. In the latter case the “customer customers” are the customer of the company. The customer of the development team is sales. Same company. Customer provides the budget that you have to fit in but

nobody ever complained that a project was under budget.

I am not talking about lower budget commitment. All projects have risks and all risks have financial impact. One way of risk mitigation is to have contingency in the budget. But again: that is the budget and not the actual spending. Still teams, departments tend to fill their budget. Why do they do that? There can be several reasons and sure I will not be able list all possible.

Reasons to spend more


The more a department spends the more important it looks. I have seen such company. The company was a large expanding company heavily investing into assets, building infrastructure for years (like telecom infrastructure, roads or railways, I won’t tell you which one) and the one who was building the more miles the better performer was. The measurement was the spent money and this culture remained when it was IT spending. Weird.


In some companies budget not spent will lessen the financing possibilities of the department for the future. If you, as a software architect can save up from the original estimates it means your estimation was not good. That will be taken into account next time you estimate. Thus the department rather wastes (usually towards end of the year) the budget left over than giving it back to treasury. It is like fixing a bug creating another. (How about unit testing departments?)


Some companies underfinance maintenance, developer trainings, education, equipment or some other IT related activities and departments tend to amend the situation from other sources: overbudgeting projects. Things certainly will happen. If you want to have something you do not pay for you will not get it. If you got it you paid for it just you do not know where, when and how much. Developers, architect, project managers may even not realize that they follow this practice in some cases. I have heard a few times the argument: “We select the more expensive technology X for the project because this way we can learn it.” This is also crossfinancing. You use the project to finance the developer’s education.

All these are bad practices. I do not need to explain the first example. The second is also quite obvious. The last one, cross financing is not that obvious.

Why cross financing is bad

When you select the more expensive technology (it may be more expensive because it has license fees, or needs more development, learning) you decide to invest the company money into something. As an architect it is not your responsibility. You may suggest that to management but you should not decide even if you are in the position that you can (unless you are also the management in a small company, but in that case you decide with your management hat on). It is only management who can decide how to invest the money. Investing into people is always a good investment even if they leave your company later. (But what if you do not invest and they stay?) But as a matter of fact management may see even more lucrative investment possibilities at that very moment.

Don’t feel bad

Do I suggest that you rush to management now and ask them to lessen your budget? Do I think that you, as a software architect should feel bad if you fill the budget and cross finance?

Not at all. I said that crossfinancing is bad practice but I did not say that it is YOUR bad practice. It is a bad practice implemented in a company. The larger the organization is the more difficult it is to change it. And it is not your task, and more importantly you may not have the capabilities to do that.

The only thing you have to: know that you follow a practice that is not optimal, so to say. If there is any chance to improve it just a little bit, go for it. Everybody making one small step will save the world.