C++ TR1: array VS 2008 Bug

Microsoft have recently released a Beta version of the Visual Studio 2008 Feature Pack which includes support for most of the C++ standard library extensions described in TR1. Alas, the beta sticker is appropriate as there are still some bugs to be ironed out.

The TR1 array container template provides functionality for implementing a fixed size array. This is a halfway point between plain old C style arrays and C++ STL vectors. The defining property of the array container is that its size is fixed. Consider and example of an array of 4 integers:

array<int,4> = { 0, 1, 2, 3 };

Since it adheres to the STL container rules, it must implement methods such as size(), and max_size(). For the array container, both of these should return the size of the array, which is fixed. In the above example, both should return 4. However, when using the VS 2008 TR1 implementation of array, a bug appears. The code:

#include <iostream>
#include <array>
using namespace std;
using namespace std::tr1;
int main()
{
    array<int, 4> arr = {1, 2, 3, 4};

    cout << "size: " << arr.size() << endl;
    cout << "max_size: " << arr.max_size() 
         << endl;
    return 0;
}

Produces the output:

size: 4
max_size: 1073741823

instead of:

size: 4
max_size: 4

If we take a look at the implementation of max_size() we can see the problem

size_type max_size() const
{    // return maximum possible length of sequence
    size_type _Count = (size_type)(-1) / sizeof(_Ty);

    return (0 < _Count ? _Count : 1);
}

Instead of simply retuning N (the size of the array), it performs the same computation as if this was a vector.

This issue has been logged as a bug with Microsoft and will hopefully be fixed before the "Gold" release of the feature pack.

C++ TR1

Effective C++, Third Edition summarizes TR1 this way:

TR1 ("Technical Report 1") is a specification for new functionality being added to C++'s standard library. This functionality takes the form of new class and function templates for things like hash tables, reference-counting smart pointers, regular expressions, and more. TR1 itself is just a document.

The TR1 draft does not contain any background information on the functionality it provides and doesn't contain any examples for how it should be used. For this sort of information refer to the proposal documents which were used to define the TR1 functionality. The relevant proposal documents are nicely catalogued by Scott Myers.

Microsoft have recently released a Beta version of the Visual Studio 2008 Feature Pack which includes support for most of the C++ standard library extensions described in TR1.

GCC v4.x also provides support for most of the extensions.

Over the next few weeks (more likely months) I plan on playing with the new TR1 features and I will add thoughts, learnings and code snippets to this blog.

Effective Concurrency ... so far

Following on from a previous post about The Pillars of Concurrency, here are links to the full set of Herb Sutters "Effective Concurrency" column topics (as of Feb 2008) ...

The Pillars of Concurrency
How Much Scalability Do You Have or Need?
Use Critical Sections (Preferably Locks) to Eliminate Races
Apply Critical Sections Consistently Avoid Calling Unknown Code While Inside a Critical Section
Use Lock Hierarchies to Avoid Deadlock
Break Amdahl's Law!
Going Superlinear

These are an excellent set of articles on the subject of concurrency and programming for multi-core that analyzes the many facets of the subject - from background theory, to locking and on to achieving scalability and performance.

Hiring Good Programmers

The company that I work for is currently embarking on a hiring spree. So I thought it would be a good idea to refresh my interviewing skills before I launch myself into the hiring process.

A recent Coding Horror entry highlights "The Years of experience myth" which is the inadequacy of trying to "match-- exactly and to the letter-- some highly specific laundry list of skills". Unfortunately when dealing with some recruitment agencies, I find this an all too common practice. Instead it is vital to remember that "... what software developers do best is learn. Employers should be loooking for passionate, driven, flexible self-educators who have a proven ability to code in whatever language -- and serving them up interesting projects they can engage with."

Joel Spolsky sums up the characteristics that employers should be looking for in future employees as "Smart and Gets Things Done".

So, now that we've figured out what to look for in a candidate, lets look at some resources that give tips for screening CVs, conducting phone screens or face to face interviews.

• The Guerilla Guide To Interviewing - Joel Spolsky gives practical and pragmatic advice on the whole process.
• Getting the Interview Phone Screen Right - because its very expensive to get it wrong.
• The Five Essential Phone-Screen Questions

And finally since the phone screen is probably the most important stage, it's worth highlighting the two common critical mistakes that an interviewer could make in the phone screen:

1. Don't let the candidate drive the interview. The interviewer should do most of the talking, guiding the conversation along until they're satisfied the candidate knows the answers to the questions (or has given up).
2. Watch out for one-trick ponies. Candidates who only know one particular language or programming environment, and protest complete ignorance of everything else, are a giant red warning flag.

» 10 techniques for gathering requirements | 10 Things | TechRepublic.com

A nice concise list of various ways to gather requirements:
» 10 techniques for gathering requirements 10 Things TechRepublic.com

When doing interviews of JAD sessions for the purposes of gathering requirements, try to ensure that you are in the same meeting room as the participants. This helps to build up a raport with the participants which generally leads to a more open dicussion which helps to produce better requirements.

Don't forget the 5 whys approach when gathering requirements. Often what a customer says he wants is different to what he needs. Dig into each requirement to fully understand why this is valuable to the customer and then ensure that the requirement is aimed at solving the root cause of the customers problem.

Is Java becoming the new Cobol?

Apparently Java is becoming the new Cobol. It comes as no surprise that .Net has emerged as the contender to to Java's throne - especially given the Miucrosoft muscle supporting and driving it. It is also pleasing to see that Ruby and Rails is emerging as a contender also. It is also pleasing to see that Microsoft are supporting the development of Ruby with its IronRuby effort to allow Ruby to run on a .Net platform.

However, Java like Cobol has built a lot of infrastructure in enterprise environments and I'm sure that this will give Java some stickiness for considerable time yet.

Reading that article makes me wonder if it will become harder and harder for new languages and computing paradigms to emerge as time goes on? Does each new language or platform need to build a weight of infrastructural components in order for it to be a successful contender for the throne? I hope not and hopefully Ruby is the latest example of a language that works and is popularised simply because developers love it!

5 Generic Debugging Tips

These are some practical tips to help maximise your chances of success when debugging software problems - especially those hard to isolate problems. Most of these tips will seem like common sense but I am constantly amazed at how often they are overlooked! I've deliberately tried to keep these at a generic level and not tie them to a specific language so that they may be of relevance to most people.

1. Think: If you can quickly build and test your application there is often the temptation to keep trying things until the bug goes away. It is easy to get caught up in a cycle of "make a change - build - test (fail) - make another change ..." without really stopping to catch your breath. The danger with this approach is that when the bug goes away it is sometimes difficult to tell if the bug is fixed or if you have just solved a symptom. Although frustrating, it is sometimes a learning experience to have to debug an application or system that takes a long time to rebuild and test. This forces you to take a step back and to think carefully about what you can glean from your current data and what the next step should be. This will help you to better understand the nature of the problem and in doing so it will help to find the root cause more quickly.
2. Baby Steps: This is a really obvious but often overlooked practice. When debugging always take baby steps and only change one thing between tests. It is often very tempting to make a couple of changes or to skip a step, but this invariably results in an inconclusive test result and you will end up backtracking to figure out which change caused a change in behavior.
3. Simplify: Try and reproduce a suspect piece of code in a stand-alone environment. For example if a particular algorithm is miss-behaving, try and replicate this behavior in a simple application that only contains the algorithm and may be easier to control and debug. Similarly, if debugging issues in a kernel, it is often possible to replicate the code at a user level which is a much more friendly debug environment.
4. Tools: Become intimately familiar with your tool chain. Take time to learn the power and quirks of your unit test environment, debugger, memory leak checker, compiler, etc. If you develop on multiple platforms and use different tool chains on those platforms then learn them all!
5. Challenge Assumptions: Assumptions can be dangerous. How many times have you assumed that a particular piece of code is working only to find you many hours later that it contained the bug that was the root cause of the issue you were debugging or that it behaved subtly different than what you expected? In general it is good practice to assume nothing and to challenge all assumptions that you find yourself making.