Category: 2010

Groovy isn’t a superset of Java

Groovy is Java with sugar, right?

Coming from Java to Groovy and seeing that Groovy looks like Java with sugar, you are tempted to write code like this:

  private String take(List list) {
    return 'a list'
  }

  private String take(String s) {
    return 'a string'
  }

But when you call this method take with null you get strange results:

  public void testDispatch() {
    String s = null
    assertEquals('a string', take(s)) // fails!
  }

It fails because Groovy does not use the declared types. Since it is a dynamic typed language it uses the runtime type which is NullObject and calls the first found method!
So when using your old Java style to write code in Groovy beware that you are writing in a dynamic environment!
Lesson learned: learn the language, don’t assume it behaves in the same way like a language you know even when the syntax looks (almost) the same.

Active Object with POCO’s Active Methods

POCO’s ActiveMethods require minimal additional code to implement the Active Object design pattern

Active Object is a well known design pattern for synchronizing access to an object and/or resource. The basic idea is to separate method invocation from method execution which is done in a dedicated thread.

Instead of using the objects interface directly, a client of an Active Object uses some kind of  proxy which enqueues a so-called Method Request for later execution. The proxy finishes immediately and returns to the client some sort of callback, or variable, by which the client can receive the result. These intermeditate result variables are also known as Futures.

As always, there are lots of ways to implement this pattern. For example, if you had an interface like this

class MyObject
{
  public:
    int doStuff(const std::string& param) =0;
    std::string doSomeOtherThing(int i) =0;
};

applying a straight forward implementation, you would first transform this into a proxy and method request classes:

class MyObjectProxy
{
  public:
    MyObjectProxy(MyObject* theObject);
    // proxy methods
    Future<int> doStuff(const std::string& param);
    Future<std::string> doSomeOtherThing(int i);
  private:
    MyObject * _myObject;
};

class MethodRequest_DoStuff :
  public AbstractMethodRequest
{
  public:
    MethodRequest_DoStuff(const std::string& param);
    // all method request classes must implement execute()
    virtual void execute(MyObject* theObject);

  private:
    const std::string _param;
};

… and so on (for more details see this basic paper by Douglas C. Schmidt, or read chapter Concurrency Patterns in POSA2).

It’s easy to see that this implementation produces a lot of boilerplate code. To solve this, you could either cook up some code generation, or look for some language support to reduce the amount of characters you have to type. In C++, some sort of template solution can be the way to go, or…

Introducing Active Methods

With class ActiveMethod together with support classes ActiveDispatcher and ActiveResult the POCO C++ libraries provide very simple and elegant building blocks for implementing  the Active Object pattern.

ActiveMethod:  this is the core piece. When called, an ActiveMethod executes in its own thread.

ActiveResult: this is what I referred to earlier as a Future. Instances of ActiveResult are used to pass the result of an ActiveMethod call back to the client.

ActiveDispatcher: if you only use ActiveMethods, every ActiveMethod thread can execute in parallel.  With ActiveDispatcher as base class, ActiveMethod calls are serialized, thus implementing real™ Active Object behaviour.

Here my earlier example using ActiveMethods:

class MyObject
{
  public:
    // ActiveMethods are initialized in the ctors
    // initializer list
    MyObject()
      : doStuff(this, &MyObject::doStuffImpl),
        doSomeOtherThing(this, &MyObject::doSomeOtherThingImpl)
    {}

    ActiveMethod<int, std::string, MyObject> doStuff;
    ActiveMethod<std::string, int, MyObject> doSomeOtherThing;
  private:
    int doStuffImpl(const std::string& param);
    std::string doSomeOtherThingImpl(int i);
};

This is used as follows:

MyObject myObject;
ActiveResult<std::string> result = myObject.doSomeOtherThing(42);
...
result.wait();
std::cout << result.data() << std::endl;

This solution requires minimal amounts of additional code to transform your lame and boring normal object into a full-fledged Active Object. The only downside is that Active Methods currently can only have one parameter. If you need more, you have to use tuples or parameter objects.

Have fun!

Avoid switch! Use enum!

Recently I was about to refactor some code Crap4j pointed me to. When I realized most of that code was some kind of switch-case or if-else-cascade, I remembered Daniel´s post and decided to obey those four rules.
This post is supposed to give some inspiration on how to get rid of code like:

switch (value) {
  case SOME_CONSTANT:
    //do something
    break;
  case SOME_OTHER_CONSTANT:
    //do something else
    break;
  ...
  default:
    //do something totally different
    break;
}

or an equivalent if-else-cascade.

In a first step, let’s assume the constants used above are some kind of enum you created. For example:

public enum Status {
  ACTIVE,
  INACTIVE,
  UNKNOWN;
}

the switch-case would then most probably look like:

switch (getState()) {
  case INACTIVE:
    //do something
    break;
  case ACTIVE:
    //do something else
    break;
  case UNKNOWN:
    //do something totally different
    break;
}

In this case you don’t need the switch-case at all. Instead, you can tell the enum to do all the work:

public enum Status {
  INACTIVE {
    public void doSomething() {
      //do something
    }
  },
  ACTIVE {
    public void doSomething() {
      //do something else
    }
  },
  UNKNOWN {
    public void doSomething() {
      //do something totally different
    }
  };

  public abstract void doSomething();
}

The switch-case then shrinks to:

getState().doSomething();

But what if the constants are defined by some third-party code? Let’s adapt the example above to match this scenario:

public static final int INACTIVE = 0;
public static final int ACTIVE = 1;
public static final int UNKNOWN = 2;

Which would result in a switch-case very similar to the one above and again, you don’t need it. All you need to do is:

Status.values()[getState()].doSomething();

Regarding this case there is a small stumbling block, which you have to pay attention to. Enum.values() returns an Array containing the elements in the order they are defined, so make sure that order accords to the one of the constants. Furthermore ensure that you do not run into an ArrayOutOfBoundsException. Hint: Time to add a test.

There is yet another case that may occur. Let’s pretend you encounter some constants that aren’t as nicely ordered as the ones above:

public static final int INACTIVE = 4;
public static final int ACTIVE = 7;
public static final int UNKNOWN = 12;

To cover this case, you need to alter the enum to look something like:

public enum Status {
  INACTIVE(4),
  ACTIVE(7),
  UNKNOWN(12);

  private int state;

  public static Status getStatusFor(int desired) {
    for (Status status : values()) {
      if (desired == status.state) {
        return status;
      }
    }
    //perform error handling here
    //e.g. throw an exception or return UNKNOWN
  }
}

Even though this introduces an if (uh oh, didn’t obey rule #4), it still looks much more appealing to me than a switch-case or if-else-cascade would. Hint: Time to add another test.

How do you feel about this technique? Got good or bad experiences using it?

Is Groovy++ already doomed?

<disclaimer>I really like Groovy and other cool languages like Scala, Fantom, Gosu or Clojure targetting the JVM.</disclaimer>

I know the title is a bit provocative but I want to express a concern regarding Groovy++. In my perception most people think of Groovy++ as an extension for Groovy which trades dynamic dispatching for static typing and dispatching yielding performance. So you can just look for hot spots in your code and resolve them with some annotations. Sounds nice, doesn’t it?.

That seems to be the promise of Groovy++ but it isn’t. Alex Tkachman, the founder of the Groovy++ project states this clearly in this comment to an issue with Groovy++: “100% compatibility with regular Groovy is nice when possible and we do our best to keep it but it is not a must.”.

Imho the mentioned issue together with this statement reduces the target audience to a few people who think of Groovy++ as a better Java, not a faster and type-safe Groovy where needed. I do not think there are too many people thinking that way. I think wide adoption of such a Groovy++ will not happen given the alternatives mentioned in the disclaimer above and Groovy itself. I hope they will strive for 100% compatibility with Groovy…

Code Camp Experiences II

A review of our first company code camp using Code Retreats like Corey Haines would do. Short summary: It was a lot of fun and we learned a lot. Go try it out yourself!

Last friday, we held a Code Camp instead of an Open Source Love Day (OSLD). We reserved a whole day for the company to pratice together and share our abilities on the coding level. While this usually already happens every now and then with pair programming sessions, this time we all worked on the same assignment and could compare our experiences. And this comparability worked great for us. This article tries to summarize our setup and the outcome of the Code Camp

Setup of the Code Camp

We tried to imitate a typical Code Retreat day in the manner of Corey Haines. If you haven’t heard about Code Retreats, Corey or the software craftsmanship idea, you could read about it in the links. The presentation of Corey at the QCon conference about software craftsmanship is also a valuable watch.

There are some resources on the internet about how to run a Code Retreat event from the organizational and facilitator’s point of view. This material gave us a good understanding of the whole event, even though our setup was different, as we had no explicit facilitator and fixed workplaces, already prepared for pair programming usage. We didn’t invite external programmers to the event, so every participant was part of our development team. We had to end the event by 16 o’clock due to schedule conflicts and started at 9 o’clock, so our retreat count would be lower than 6 or even 7.

Basically, we tried to program Conway’s Game of Life within 45 minutes in pairs of two developers repeatedly. After the 45 minutes have passed (supervised by an alarm clock), we deleted the code and gathered for an iteration review of 15 minutes. Then, we started over again. This agenda should repeat throughout the day. No other activity or goal was planned, but we anticipated a longer retrospective meeting at the end of the day.

Execution of the Code Camp

The team gathered at 9 o’clock and performed setup tasks on the computers (like preparing a clean workspace). At 09:15, we held an introduction meeting for the Code Camp. I explained the basics and motives of Code Retreats and presented the rules for Conway’s Game of Life. The team heard most of the information for the first time, so nobody was particularly more experienced with the task or the conduct.

The first iteration started at 10 o’clock and had everybody baffled by the end of the iteration. The first retrospective meeting was interesting, as fundamental approaches to the problem were discussed with very little words needed for effective communication. Everybody wanted to move into the second iteration, which started at 11 o’clock.

At the end of the second iteration, two of the four teams nearly reached their anticipated goals. In the retrospective, the results were incredibly more advanced compared to the first iteration. This effect was similar to my first code camp: The second iteration is the breakthrough in the problem domain. Afterwards, the solutions are refined, but without the massive boost in efficiency compared to the other iterations except the first one.

We went to lunch early this day and returned with great ideas for the next round. After a short coffee break with video games, we started at around 13:45 for the third iteration.

The third iteration resulted in the first playable versions of the game. The solutions grew more beautiful and the teams began to experiment with their approaches, as the content-related task was mentally covered. This was the most productive iteration in terms of resulting software. But as usual, the code was deleted without a trace directly after the iteration. The iteration review meeting brought up a radically different approach on the problem as previously anticipated. This inspired every team for the fourth iteration.

In the fourth iteration, every team tried to implement the new approach. And every team failed to gain substantial ground, just like in the first iteration. The iteration review meeting was interesting, but we skipped another iteration in favor of the full retrospective of the Code Retreat.

Effects of the Code Camp

The Code Retreat iterations had great impact on our team. We discussed our impressions informally and then turned back to the formal retrospective questions as suggested by Alex Bolboaca:

  • How did you feel?
  • What have you learned?
  • What will you apply starting Monday?

The first question got answered by a “mood graph”, rising steadily from iteration one to three, with a yawning abyss at iteration four. This was another strong indicator that the iterations sort of restarted with iteration four.

The second question (“What have you learned?”) was answered more variably, but it stuck out that many keyboard shortcuts and little helpful IDE tricks were learnt throughout the day. We tracked the origin and propagation of two shortcuts and came to the result that one developer knew them beforehands, transferred the knowledge to the partner in the first iteration and both spread it further in the second iteration. By the end of the third iteration, everybody had learned the new shortcut. It was impressive to see this kind of knowledge transfer in such a clear manner.

The third question revolved around the coolest new shortcuts and tricks.

But we learned a lot more than just a few shortcuts. Most of all, we had a comparable coding experience with every other developer on our team. This isn’t about competition, it’s about personality. And we’ve found that the team works great in every combination. Some subtle fears of “being behind with knowledge” got diminished, too.

Future of the Code Camp

Everybody wants to do it again. So we’ll do it again. We decided to perform one Code Camp every three months. This isn’t too often to wear off, but hopefully often enough to keep our practice level high. We also decided to run dedicated Code Camps with external developers soon. The first event will happen in December 2010.

Shrink your dependency list with POCO

POCO is a nice set of C++ libraries which provides elegant solutions for day-to-day tasks.

When you write C++ applications of any sort you are very likely to need support libraries in addition to what comes with C++ (which is not much, btw). Of course, this holds true for any other language. But with Java and its rich JDK for example this need is not so imminent.

Starting at the very beginning, let’s see how fast the need for support arises.

int main(int argc, char** argv)
{
// parsing command line arguments
...

How to parse those command line arguments in a simple and easy way? How about a little help output when the program is called with -h or –help? Ok, we got boost::program_options for this.

Going further in your program you may want to have some sort of logging capability. Unfortunately, as of boost version 1.45 there is nothing to be found there. So you add a nice logging library.

And so on.

But wait! You don’t want to depend on too many 3rd party libraries because, among other things, they add deployment complexity.

Not even Qt, as one of the major players in the C++ framework world, provides solutions to both previous examples. As of version 4.7, no logging and not much support with command line arguments. And you end-up having to use QString, one of many non-std::string classes in C++ frameworks, which can get annoying at times (of course there are reasons why those exist).

I could go on with the list of smaller or larger concerns for which you either roll your own implementation or include yet another library in your project.

Instead I would like to point you to POCO, a nice set of C++ libraries which provide easy solutions for many basic and/or advanced day-to-day tasks. From their website:

Modern, powerful open source C++ class libraries and frameworks for building network- and internet-based applications that run on desktop, server and embedded systems

Besides very basic stuff like logging, date/time handling, threads, memory management, UTF-8, etc. they also provide lots of higher level classes for things like SMTP, POP3, SQL database access and HTTP. They even have a so called C++ Server Page Compiler which is basically something like JSP or Active Server Pages.

And they have no own string class! Yay! Instead they provide lots of functions classes and streams to do string manuipulation on good old std::string.

One thing I like most about POCO, though, is its clean, well-documented and apparently very high quality code. Although it is not overly functional or template-heavy, like you see it in in boost very often, it still provides elegant solutions.

Check it out and shrink your dependency list.

Diving into Hibernate’s Query Cache behaviour

Hibernate is a very sophisticated OR-Mapper and as such has some overhead for certain usage patterns or raw queries. Through proper usage of caches (hibernates featured a L1, L2 cache and a query cache) you can get both performance and convenience if everything fits together. When trying to get more of our persistence layer we performed some tests with the query cache to be able to decide if it is worth using for us. We were puzzled by the behaviour in our test case: Despite everything configured properly we never had any cache hits into our query cache using the following query-sequence:

  1. Transaction start
  2. Execute query
  3. Update a table touched by query
  4. Execute query
  5. Execute query
  6. Transaction end

We would expect that step 5 would be a cache hit but in our case it was not. So we dived into the source of the used hibernate release (the 3.3.1 bundled with grails 1.3.5) and browsed the hibernate issue tracker. We found the issue and correlated it to the issues HHH-3339 and HHH-5210. Since the fix was simpler than upgrading grails to a new hibernate release we fixed the issue and replaced the jar in our environment. So far, so good, but in our test step 5 still refused to produce a cache hit. Using the debugger strangely enough provided us a cache hit when analyzing the state of the cache and everything. After some more brooding and some println()'s and sleep()‘s we found the reason for the observed behaviour in the UpdateTimestampsCache (yes, yet another cache!):

	public synchronized void preinvalidate(Serializable[] spaces) throws CacheException {
		//TODO: to handle concurrent writes correctly, this should return a Lock to the client
		Long ts = new Long( region.nextTimestamp() + region.getTimeout() );
		for ( int i=0; i
			if ( log.isDebugEnabled() ) {
				log.debug( "Pre-invalidating space [" + spaces[i] + "]" );
			}
			//put() has nowait semantics, is this really appropriate?
			//note that it needs to be async replication, never local or sync
			region.put( spaces[i], ts );
		}
		//TODO: return new Lock(ts);
	}

The innocently looking statement region.nextTimestamp() + region.getTimeout() essentially means that the query cache for a certain “region” (e.g. a table in simple cases) is “invalid” (read: disabled) for some “timeout” period or until the end of the transaction. This period defaults to 60 seconds (yes, one minute!) and renders the query cache useless within a transaction. For many use cases this may not be a problem but our write heavy application really suffers because it works on very few different tables and thus query caching has no effect. We are still discussing ways to leverage hibernates caches to improve the performance of our app.

Open Source Love Day October 2010

Our Open Source Love Day for October 2010 brought love for the cmake hudson plugin. Other issues were addressed but not finished. If you like to type fast and accurate, we suggest you check out typeracer.

On Friday two weeks ago, we held our Open Source Love Day for October 2010. This day was special in several ways. We strayed very far from the usual schedule for this day, there were several internal tasks that couldn’t be delayed and we introduced a “fun practice” event. But we eventually produced something valuable this day.

The Open Source Love Day

We introduced a monthly Open Source Love Day (OSLD) to show our appreciation to the Open Source software ecosystem and to donate back. We heavily rely on Open Source software for our projects. We would be honored if you find our contributions useful. Check out our first OSLD blog posting for details on the event itself.

The distractions

  • A regular project needed an urgent cost estimation by the whole team. This was the last opportunity because of an upcoming parental leave to have the team together for a long time.
  • Another regular project needed an urgent problem solved. This turned out to be so obscure that one of our developers had to be on-site. You can read about it in this blog entry now.
  • We received several shipments of office furniture and computer parts. They had to be checked and placed in.
  • We had a fun practice event. We discovered the online “game” typeracer and practiced our raw typing skill against each other for some time. Pro tip for beginners: don’t look at the highscores!

On this OSLD, we accomplished the following tasks:

  • A new version 1.8 of the cmakebuilder hudson plugin implements several feature requests. You can now choose to NOT clean your workspace before building and set different paths for the cmake installation for every job or node (hudson slaves). The latter option can be applied using an environment variable.

On this OSLD, we also tried the following tasks:

  • We keep an eye on Scala and its associated web framework Lift as a promising technology. One issue with Lift that bugs us is the use of “sun bastard format” properties for internationalization. We tried to teach Lift to accept UTF-8 encoded property files. After a lot of “downloading the internet” (you can always tell which project uses maven by their initial setup delay), we quickly implemented our own ResourceBundle.Control. But the Lift framework itself could not be built: “Error occurred during initialization of VM: Could not reserve enough space for object heap”. We ran out of time and will investigate in this issue on the next OSLD.
  • Grails is another web framework we use in projects. There are some bugs that really annoy us, and the OSLD is the perfect time to fix them. One of these bugs is GRAILS-6475, which we tried to reproduce with the latest code base. After writing a test case that would go green unexpectedly, we tried to provoke the error by setting up a sample project. The bug didn’t show up there, too. We left a comment in the issuetracker and ceased development.

What were our lessons learnt today?

  • You can’t tear off massive amounts of time from the OSLD and expect it to still be working. An OSLD doesn’t scale down apparently.
  • Most issues that can’t be done fail with the project’s build. The build process of a foreign project is the most crucial phase in your decision on commitment. If it fails, your participation in the project is at risk. We’ve seen many brittle, undocumented and incredible complex build processes now. And we can state one thing: It doesn’t stop with throwing maven at a project, you still have to “think the build”.

Retrospective of the OSLD

This OSLD was special in the amount of non-OSLD work done. The remaining efforts weren’t as successful as we wished. This has been an ongoing issue with our OSLD for the last months now and we are looking forward to adapt our workstyle to yield better results in the future. The distraction by typeracer was fun, though.

An advent of unconditional quality code

A four-week experiment dealing with conditional statements and how to avoid or replace them. Starting at the first advent, the experiment runs until christmas. We invite you to join and share your experiences.

This blog entry invites you to an experiment in code. It’s an experiment that runs four weeks and can be performed secretly even at your workplace. It might improve the way you think about conditional statements in an object oriented programming language. You don’t need any special hardware or setup, just the will to change your coding style a bit each week.

The experiment

Beginning with this year’s advent (a season of the christian religion), you are asked to omit one type of conditional statement each week while programming your regular code. The omitted statements add up, so that you have to spare four different statements in the week before christmas. There is no relation to christmas (or religion) other than it’s a four week period at the end of the year, which is the perfect timeframe for the experiment. And you might buy yourself a little present for christmas if you succeeded at the experiment (idea: a new programming book).

The four stages

For every stage, you are asked to write your normal code without a specific statement. It is perfectly valid to use semantically equivalent code constructs to achieve the same goal. This experiment is even more successful if you are creative and diversified in your variations of the original statement. Remember that the stages add up. On the fourth stage, you are asked to use none of the statements mentioned below.

  • Stage 1 (first week): Don’t use “else”
  • Stage 2 (second week): Don’t use the conditional operator “?:”
  • Stage 3 (third week): Don’t use “switch”
  • Stage 4 (fourth week): Don’t use “if”

You are not asked to change existing code to conform to these restrictions, except you need to work on the lines that contain the prohibited statements. You should apply the rules to your new code rigorously, though.

Explanation of stage 1 (Don’t use “else”)

This rule bans all the different occurrences of the else-branch to your if-statements. It includes every “else if” or “elsif” your programming language might provide. The rationale behind the rule can be found in the Object Calisthenics, rule #2 by Jeff Bay. Here is an explanation of it by Being Cellfish.

Explanation of stage 2 (Don’t use the conditional operator “?:”)

Elvis is dead. Let this resemblance to his hairdo rest for a week, too. It contains a hidden else statement that is restricted since stage 1. Another rationale is that the conditional operator isn’t very easy to read/grasp if stretched out a long line.

Explanation of stage 3 (Don’t use “switch”)

A switch (or case, or select) statement is nothing but a big if-else cascade. It’s handy sometimes, but can be replaced by a lookup table (like a hashmap) virtually everytime . In Martin Fowler’s book “Refactoring”, the switch statement counts as its own code smell category. You should try to live without it for a week. If you need inspiration, try this article on how to avoid it.

Explanation of stage 4 (Don’t use “if”)

Yes, you didn’t misread. There is a whole campaign that tries to avoid the if-statement altogether. Read their website for inspiration on how to survive this week. Maybe you might make new friends with polymorphism and some other implicit conditional structures. Remember, this is a short week just before christmas. Try it, you might be surprised how easy it looks with hindsight.

Ready, steady, go!

This experiment starts with the first advent at Sunday, 28.11.2010. Every stage lasts for one week and adds up to the previous stages. The experiment ends at christmas.

Good luck! And if you’re done with it, drop us a comment with your experiences.

Bug hunting fun with std::sort

Small errors in custom comparison functions used with std::sort can lead to hard-to-find bugs.

The other day I came across a nice little C++-shoot-yourself-in-the-foot at one of our customers. Let’s see how fast you can spot the problem. The following code crashes with segmentation fault sometime, somewhere in the sort call (line 31).

#include <iostream>
#include <vector>
#include <boost/shared_ptr.hpp>
#include <boost/bind.hpp>

using namespace std;
using namespace boost;

enum SORT_ORDER
{
  SORT_ORDER_ASCENDING,
  SORT_ORDER_DESCENDING
};

bool compareValues(const std::string& valueLeft,
                   const std::string& valueRight,
                   SORT_ORDER order)
{
  const bool compareResult = (valueLeft < valueRight);
  if (order == SORT_ORDER_DESCENDING) {
    return !compareResult;
  }
  return compareResult;
}

int main(int argc, char *argv[])
{
  std::vector<std::string> strValues(300);
  std::fill(strValues.begin(), strValues.end(),
            "Hallo");
  std::sort(strValues.begin(), strValues.end(),
            bind(compareValues, _1, _2, SORT_ORDER_DESCENDING));
  return EXIT_SUCCESS;
}

Any ideas? The tricky thing about this bug is that the stacktrace output in the debugger gives absolutely no hint at all about its cause. And this is a simplified version of the real code which has to sort boost::shared_ptrs instead of strings. Believe me, you don’t want to see that stacktrace. Because of the use of boost::bind together with boost::shared_ptrs it looks, well, let’s say intimidating.

Still no idea?

I’ll give you a hint. If the SORT_ORDER is set to SORT_ORDER_ASCENDING everything is fine. …

Ok, the problem is that std::sort algorithm must be given a comparison function (object) that defines a strict weak ordering on the elements that are to be sorted. In other words the comparison function object must implement the ‘<‘ (less than) relationship on the elements.

Unfortunately, lines 20 to 22 break this ordering when SORT_ORDER_DESCENDING is given. The initial idea of this code was that, well, if compareResult gets returned on ascending sort order, lets just return the negation of it when the “negation” of acscending order is requested. This, of course, destroys the strict weak ordering requirement because whenever valueLeft == valueRight, the function returns true, meaning instead that valueLeft < valueRight. And this somehow wreaks havoc inside std::sort.

A better version of the function could be:

...
bool compareValues(const std::string& valueLeft,
                   const std::string& valueRight,
                   SORT_ORDER order)
{
  // solution: return false independent of sort order
  // whenever valueLeft == valueRight
  if (valueLeft == valueRight) {
    return false;
  }
  const bool compareResult = (valueLeft < valueRight);
  if (order == SORT_ORDER_DESCENDING) {
    return !compareResult;
  }
  return compareResult;
}
...

The really annoying thing about this whole issue is that std::sort just randomly crashes with a stack trace that shows nothing but some weird memory corruption going on. After the initial shock, this sends you down the complete wrong bug hunting road where you start looking for spots where memory could be overwritten or the like.

So beware of custom comparison functions or function objects. They might look innocent and easy, but they can give you lot’s of headaches.