People Patterns In Software Development: The Programming Hipster

“That proves you are unusual,” returned the Scarecrow; “and I am convinced that the only people worthy of consideration in this world are the unusual ones. For the common folks are like the leaves of a tree, and live and die unnoticed.”
— L. Frank Baum, The Marvelous Land of Oz

After a series of rather technical posts, I feel a strong urge to release some lighter reading. Let me introduce a new series called “people-patterns in software development” (PPSD).

As a freelance software developer, I’ve met literally hundreds of people over the years. People are individuals, of course, and no two people are the same, but I have observed that certain personalities traits — personality patterns — appear over and over again. What an amazing zoo we live in!

The goal of PPSD is to collect and classify these personalities, to provide a taxonomy in an exaggerated, tongue-in-cheek way.

If you, dear reader, have also come across “outstanding” personalities and want to contribute to this compilation, don’t hesitate and drop me a line! Without further ado, let’s get started with our first personality pattern, the Programming Hipster.

PROGRAMMING HIPSTER

If I had to pick one characterizing adjective that describes a Programming Hipster best it would be “different”. Programming Hipsters have one distinct goal: to be different from the pack and they demonstrate this not only by behavior but also by appearance. A Programming Hipster is the opposite of the average, boring mainstream developer, aka. John C. Coder.

A Programming Hipster is male and usually only found in small, software-centric companies, mostly startups where the average age is below 30. You rarely find him in medium-to-large environments, because his style is way out of line with what typical corporate identity standards demand.

Classical examples of Programming Hipsters are the founding fathers of Unix, like Dennis Ritchie and Ken Thompson. Here is an illuminating quote from “The Art of Unix Programming” by Eric Steven Raymond:

“The pioneering Unix programmers were shaggy hippies and hippie-wannabes. They delighted in playing with an operating system that not only offered them fascinating challenges at the leading edge of computer science, but also subverted all the technical assumptions and business practices that went with Big Computing. Card punches, COBOL, business suits, and batch IBM mainframes were the despised old wave; Unix hackers reveled in the sense that they were simultaneously building the future and flipping a finger at the system.”

APPEARANCE

What does a programmer look like that wants to be different? Usually, programmers already look different, at least compared to average business people: instead of suit and tie they prefer casual clothing like t-shirts, jeans, and sneakers; by and large they don’t care much about looks. The Programming Hipster, however, wants to be clearly discernible from his peer programmers and appearance matters a lot him. The clearest signs of a Programming Hipster are:

1. Either long hair, especially pony-tailed long hair or shaved head.
2. A monumental full beard.
3. Shorts worn in wintertime.
4. Woolen hats worn in summertime.
5. A big headphone, worn all day, even when visiting the bathroom.

Even a single match from this list is a strong indication that a person is a Programming Hipster; more than one is 100% proof.

PERSONALITY TRAITS

Programming Hipsters care a lot about their craft and their technical and programming skills are clearly above average. The same can be said about their intelligence. They are characterized by high-self esteem and usually hold strong opinions. They are not the easiest people to get along with. Most of them can be considered lone wolves that shouldn’t be mixed with the herd. Some of them are team-players, but most of them are not. Thus, Programming Hipsters mostly work on projects where all members have the exact same values and opinions; that is, single-person projects. The biggest shortcoming of a programming hipster is — you guessed it — his ego.

TOOLING

In almost all cases, Programming Hipsters are keyboard virtuosi and disgusted by mice.

To them, only Vi and Emacs deserve to be called “editor”, provided that the color scheme is set to dark. Every other so-called “editor” is just “Notepad” or a derivative of “Notepad”, which, like any other product originating from Redmond, is miles beneath them.

Consequently, they prefer CLIs (Command-Line Interfaces) and use GUIs (Graphical User Interfaces) only when forced to. Since Bash is so prevalent (“mainstream”), they favor a highly-customized version of zsh.

Programming Hipsters pick programming languages from the lower end of the Tiobe index (e. g. Rust) but their ideal programming language doesn’t even appear on the index (e. g. Haskell). Mainstream languages like Java, C, C++, even Python are generally frowned-upon, even though I remember that one Hipster Programmer lowered himself to participate in a C++11 project (subject to the condition that he may use some advanced features from boost and the not-yet-released C++20 standard).

RATING

According to the Q²S² framework, a Programming Hipster’s rating is 4/4/2/2.

CONCLUSION

A Programming Hipster is a colorful addition to every software company, they are the parrots among the sparrows. It would be a mistake to assign such extravagant persons to mundane product development projects; they will, however, excel if they work on prototypes or bleeding-edge research projects.

Code Kata 5: Reversing The Bits

“Boredom is just the reverse side of fascination: both depend on being outside rather than inside a situation, and one leads to the other.”
— Arthur Schopenhauer

Winter is definitely approaching. The days are getting shorter and temperatures are dropping. Isn’t this a wonderful time for doing code katas? Sitting in your easy chair, in front of a fireplace, serenely coding away in your favorite editor.

Today, we dip once more into the realm of low-level embedded programming. Your primary job is to write code that reverses the bits of an integer. For instance, reversing the 8-bit integer value 139 (10001011) yields a new value of 209 (11010001).

Sounds simple, doesn’t it? But it’s not just about coding a bit-reversing routine, that wouldn’t teach you enough lessons. You’ll also practice unit testing, code tuning and — if you like — assembly language programming, cross-compilation, and remote debugging along the way.

The goal is not to find the best/fastest algorithm possible. Instead, the emphasis is on exercising your programming muscle and learning new things. Don’t rush this kata, rather consider it a mini project. Do the research, be persistent. Try and fail and become better. Take your time, I did it over a period of three weeks. Now, without further ado, let’s get (gently) started.

1. Implement a bit reversing function in a dynamic programming language (eg. Perl, Ruby, Python).

a) Decide on a suitable interface, eg. in Python, it could look like this:

b) Implement a dummy version of ‘reversebits’ that simply returns 0.

c) Implement a couple of test cases, run them against the dummy version and watch them fail, eg.

d) Implement a straightforward solution (‘reversebits1’) that passes the unit tests.

e) Add more unit tests to gain better confidence in your solution.

f) Measure the execution time of ‘reversebits1’.

g) Be creative, find other solutions. Optimize for speed, optimize for shortest code (in terms of characters typed). Measure and compare the execution times.

h) What if ‘max_bits’ is smaller than the total number of bits already taken-up by ‘value’? For instance

In this case, only the first ‘max_bits’ of ‘value’ shall be reversed and the remaining upper bits shall be discarded:

Adapt your code accordingly. Probably, some of your solutions already behave correctly and need no modifications.

2. Port your code and unit tests to C/C++

a) Decide on a suitable interface. It’s OK if you use a fixed-bit unsigned integer data type for the value to be reversed, as long as it supports at least 32 bits, eg.

b) Measure execution times and compare them against the execution times from 1.

c) Play with various compiler optimization settings. How do they impact the timings?

d) Bonus: Implement a bit reversal function in x86 assembly language.

3. Port your code and tests from 1. and 2. to a Raspberry Pi

a) Don’t have a Pi? Find out how to emulate one on your PC.

b) Measure and compare execution times using various optimization settings.

c) Bonus: Implement a bit reversal function in ARM assembly language.

d) Bonus: Want to learn even more? Build your own cross toolchain (hint: ‘crosstool-ng’) and build the Pi code on a regular PC. Debug the code remotely over a TCP connection (hint: ‘gdbserver’, ‘gdb-multiarch’).

I certainly learned a lot by doing this kata. Far more, than I can possible tell here without risking to bore you and/or spoil all the fun. Nevertheless, I uploaded my work to GitHub. Have a peek in case you get stuck, need some inspiration or are just curious.

‘static’ With Array Parameters? Oh My!

There’s a rather obscure feature in C99 which allows you to put the ‘static’ keyword between the brackets when declaring array-like parameters to functions, as in

What this means, in a nutshell, is that the caller of this function is expected to pass an array of at least 42 uint8_t’s. Calling ‘transform’ like this would be perfectly OK:

whereas this would constitute a breach of contract:

Likewise, passing a NULL pointer is not allowed, as it — by definition — doesn’t point to anything, not even a single element:

THE QUEST FOR MEANING

While the semantics of this feature are pretty clear, the purpose isn’t. The C99 language standard doesn’t give a hint, either.

Even when ‘static’ is used, the called function ‘transform’ doesn’t know the exact size of the array. It only knows that it comprises at least 42 elements, so it can only reliably utilize 42 elements. There’s nothing ‘transform’ can do with any (potential) extra elements, because there might be none. So what’s different to this?

This question haunted me for days (if not weeks) and I just couldn’t find a satisfying answer. But let’s put it aside for a moment, as I still have a lot to critisize regarding the technicalities.

THE SYNTAX

First off, why on earth ‘static’? In C, the keyword ‘static’ has already overloaded meanings: a) module scope (an object or function declared ‘static’ is private to a translation unit) and b) lifetime (a static object defined within a function retains its value across invocations). Thanks to C99, ‘static’ now can also mean “at least”. Yuck!

Had I been forced to specify this feature, I would have used the ‘>=’ operator instead of ‘static’:

THE DANGERS

One of the biggest and most infamous blunders in engineering is when you don’t have a single point of truth; that is, the same information is stored in more than one place. Over time, inconsistencies arise in the copies which can lead to all kinds of havoc. All software engineers are reminded again and again to honor the DRY principle.

According to the grammar, ‘static’ can appear in function declarations as well as function definitions. Nobody prevents you from declaring ‘transform’ like this in your header file:

and like so in a C file:

The C99 standard says nothing about such inconsistencies, whether it constitutes an error, which one takes precedence, whether the compiler has to emit a warning message.

Another problem is that C99 also introduced variable-length arrays (VLAs) and hence an array’s size is not required to be a compile-time constant, like it used to be in C89 and like it still is in C++. Therefore, the C99 grammar blesses such abominations:

What’s the contract now? At least 42 elements (the value of ‘my_global’ at program start-up) or the value of ‘my_global’ when ‘transform’ is actually called:

Again, if you’d forced me to specify this feature, I’d required the size specifier to be a compile-time constant:

AN EPIPHANY

While ranting about this feature, I suddenly had an epiphany. Let’s revisit the question I asked above: What’s really the difference between

and

since my doubts regarding the usefulness of this feature are 100% founded in this question. Previously, I believed that in the second case, there are at least 42 elements, while in the first case there are exactly 42 elements. Not a big difference, because what benefit would a compiler be able to derive from this subtle difference?

But I obviously fell into a trap that I warned my readers a long time ago: believing that array parameters are really arrays, which is mistaken, of course, because arrays cannot be passed directly to functions. From the C language’s point of view, the former interface of ‘transform’ is equivalent to

which means that ‘buffer’ is a pointer to a single ‘uint8_t’, nothing more, nothing less. The compiler can’t make any assumptions beyond that, it’s obliged to ignore the fact that you indicated that there are 42 elements. Specifically, all these declarations are equivalent and effectively declare a function taking a pointer to a ‘uint8_t’:

By contrast, the version of ‘transform’ that uses ‘static’ tells the compiler that a pointer to the first of at least 42 elements is passed. Armed with this knowledge, the compiler can now perform certain optimizations, the most likely one being accessing memory in units much larger than a ‘uint8_t’, to save memory access times. Ah!

ADVICE

Even though we now understand the motivation behind this feature, I still wouldn’t recommend using it. Just like it’s the case with many other so-called “optimization” features (e. g. ‘inline‘ and ‘restrict‘) you, as a developer, have to keep a promise but get nothing dependable back from the compiler. As usual, my advice is this: if you think something needs to be optimized, prove it first; if evidence shows that optimization is necessary, optimize in a dependable way — don’t rely on something that might change from one compiler version to another, especially if it comes with an hideous interface that invites inconsistencies.

ONE MORE THING

Thinking about this odd feature once again, what it all boils down to is that ‘static’ with function parameters actually tries to deliver what regular array-like parameters can’t, namely inform the compiler that the pointer that is passed is really an array, not just a pointer to a single element. But there’s already a feature in the C language (available since C89) that achieves that, namely pointers to arrays:

Contrary to ‘static’ with array parameters, pointers to arrays is a clean, proven, and type-safe concept. Since the compiler knows how many elements the array comprises, it can apply the same optimizations that the ‘static’ with array parameters feature promises, that is, accessing multiple elements at once when traversing the array. There’s really no reason to put ‘static’ between your array brackets, trust me.

Alternative Representations in C and C++

When you go back to C/C++ after a week of coding in Python, funny things can happen. I already described such a case in this post.

Recently, I had another surprising incident. I was scanning my code changes in order to find a bug that had pestered me for quite a while. I rubbed my eyes in disbelief when I came across this ‘if’ statement:

How could this even compile? Instead of ‘&&’ I inadvertently typed ‘and’, the Python logical ‘and’ operator. At first, I thought that this must either be a g++ extension or some clever guy* had defined

somewhere in a header file that I pulled. Being biased towards the second theory, I did an experiment and undefined ‘and’ just before my ‘if’ statement:

but it didn’t compile. Luckily, the compiler message that I got from g++ unraveled the mystery:

Whoa! ‘and’ is an operator (a token) in C++ that hitherto I’d never heard of. In fact, there’s a whole bunch of what the C++ standard calles “alternative tokens” (or sometimes “alternative representations”):

Alternative Token Equivalent To
and &&
and_eq &=
bitand &
bitor |
compl ~
not !
not_eq !=
or ||
or_eq |=
xor ^
xor_eq ^=

It didn’t take long and the feeling of surprise was replaced with a feeling of disappointment. Some of the bit-wise operators have a ‘bit’ prefix while others don’t. ‘and’ and ‘bitand’, for instance, but ‘and_eq’ should actually be ‘bitand_eq’, because ‘&=’ is a bitwise operator — sigh! The same goes for ‘or’, ‘bitor’ and ‘or_eq’. By the same token (pun intended!), ‘xor’ and ‘xor_eq’ should really be ‘bitxor’ and ‘bitxor_eq’, if you’d ask me.

Not so confusing, actually quite beneficial, are the operators ‘and’, ‘or’, and ‘not’ by themselves. Consider:

While using these newly discovered keywords is certainly not a huge thing, I do believe that alternative operators are more readable than their cryptic, traditional counterparts. Habitually used, they even avoid classic blunders like forgetting to put a second ‘&’ or ‘|’ in logic expressions. I think I’ll give them a try — but this time as a deliberate act, instead of a Freudian slip like last time.

Note, however, that in C, these alternative representations don’t exist as keywords. Instead, they are defined in iso646.h as macros — just like the “clever guy” would have done it :-)

________________________________

*) Once, such a “clever guy” made fun of our team’s coding standard by defining this macro (the letter O) in a global header file:
#define O (1 – 1)
and using ‘O’ in his code whenever he needed a literal ‘0’ (zero):
for (int i = O; i < max; ++i) {

}
When I asked him why on earth he did such an insane thing, he replied, “Well, our coding standard says that we MUST not use octal literals, but 0 is an octal literal since it starts with a ‘0’. Smartass!

The Happy Path to Modern C++

“Show the readers everything, tell them nothing.”
― Ernest Hemingway

Considering all the C++ job offers that I’ve received over the last couple of months, it looks like modern C++ (any C++ release beyond C++03) is picking up momentum, especially in embedded systems. Why embedded systems? I think it’s because C++ has always put a lot of emphasis on efficiency and thus the features offered by C++11 and C++14 not only simplify a programmer’s life but also stand a good chance of yielding more performant code. Now that C++11 and C++14 are supported by almost all contemporary compilers, there’s no reason to hold back anymore.

Alas, reading standard documents or even books on the subject is no fun. While the idea behind new features is usually easy to grasp, there are often intricacies that dim a feature’s shine. Clearly, studying books and learning about subtleties is necessary at some point, but isn’t there an accelerated way to get started (or motivated)?

Now there is, at least that’s my goal with this new project that I’ve created: The Happy Path to Modern C++. The idea is to tackle modern C++ by example not by text; that is, by code snippets that demonstrate the beauty of language features, not their nitty-gritty details.

Every code snippet can be compiled and run in a debugger to explore its behavior. Thus familiarizing (and experimenting) with modern C++ language features should be painless (maybe even fun?).

Let me show you what I mean. The following snippet (which is part of cpp11/01_core_features/core_features.cpp) introduces range-based for-loops:

Just go to cpp11/01_core_features and execute

to compile the code and

to run it.

With this set-up, it’s easy to toy around: just uncomment the line in ‘test_range_based_for_loops’ that constitutes a syntax error (the line that attempts to modify the read-only variable), rerun make and see what happens. Contrast this hands-on approach with the (fine) documentation on cppreference.com, which is exact and comprehensive (and ten times more readable than the official language standardese), but nevertheless intimidating for beginners.

Be aware that you are looking at work in progress. My aim of this first release was to cover most of C++11 and C++14 core language features as well features pertaining to classes. Obviously, a lot is still missing, like

– Const expressions
– Variadic templates
– Lambdas
– Concurrency
– Move semantics
– Regexps

Contributions to this project are more than welcome, just send me your pull requests. Please keep in mind that the overall goal is to have crisp code examples that capture the essence of features, not the ugly corner cases. When in doubt, leave it out, keep it simple, keep it beautiful.

How To Hire Great Developers, Part I

“When there is a will, there is a way.”
— Unknown

Hiring great software developers is certainly not an easy task. To find out if a candidate is a good fit, companies usually focus on assessing an applicant’s knowledge, social skills, and intelligence.

THE STATE OF THE ART

Knowledge means that a person has a profound command of the domain, technology, and tools required for his/her job. If, for instance, you need a C++ developer for the development of an ECU (electronic control unit) for a car, you probably want somebody who is not only proficient in C++, but also has expert knowledge of embedded systems development, Autosar (an automotive middleware), CAN/FlexRay/MOST (some automotive communication buses), and probably a lot more technologies and tools. Determining a candidate’s level of knowledge is straightforward: you just need to ask enough technical questions.

Since today’s projects are usually done by teams, not individuals, social skills are very much sought after by every company. In general — and contrary to what is portrayed in Hollywood movies — software developers aren’t those pizza-eating and Red-Bull-drinking loners that reverently stare at their screens all day (and night). While such stereotypical coders do exist, they are the rare exception. These days, most professional software developers spend a significant share of their time communicating with peers, managers, and sometimes even customers. Developers need to successfully explain, present, and negotiate. Being able to do this in an open and respectful manner is not just highly desirable — it’s an essential survival skill. How to find out if a person has social skills? You ask questions and pay attention to how things are said and presented. Have candidates talk a little bit about themselves, their past projects, let them explain a difficult topic.

Many traditional companies would stop here. However, most successful, especially software-centric companies have recognized that while knowledge is important, it’s not sufficient. They want smart developers; that is, developers that come up with creative, efficient solutions and require little time to implement them. Thus, they also check a candidate’s intelligence by torturing them with riddles and logic puzzles, including those who look like they’re impossible to solve (“How Would You Move Mount Fuji?“). Others ask candidates to do online programming tests that challenge the candidate to find clever solutions to tough programming problems. The reasoning is this: intelligence ensures that knowledge is put to good use.

By now you know whether your candidate is a great developer, don’t you? If a candidate passes all the aforementioned tests, (s)he certainly has a lot of ability. But does this also imply that such a person will get the job done? Sadly, it’s a common fallacy to confuse ability with willingness.

MY HERO

More than fifteen years ago, I worked on project where the development team received insanely formatted error log files from the testing department. Information that would have helped us debug the problem was buried deeply in ASCII noise. Every time we received a bug ticket, we had to spend quite some time on figuring out what exactly went wrong. One day, a coworker gleefully came into my office and told me that he’d written a filter program that extracted and reformatted all the relevant data from the error log files. What a neat idea and what a time-saver! Full of pride, he showed me his code. What I was faced with was many pages of C code, written over the course of three days, full of low-level ‘getc’-based text parsing — definitely not easy on the eyes! Finally, I gave him a smile and thanked him for this great little tool. Half an hour later I went to his office and showed him a 30-line Perl listing that was functionally equivalent to his C code.

He didn’t know about regular expressions and neither Perl nor any other scripting language. All he knew was C. He clearly lacked knowledge. He was a lousy software developer, right?

As a matter of fact, I think he was a very fine developer. None of the other team members (including myself) — despite knowing about regular expressions and Perl — could be bothered implementing such a productivity boosting tool. Instead of lamenting, he just did it, even though it must have been painful for him. He didn’t waste three days because of his incompetence. His persistence saved hundredths of developer-days down the road. He did it because it was the right thing to do.

Of course, he was somewhat embarrassed at first. I told him that I reimplemented his program to demonstrate the power of regular expressions and dynamic languages, not to insult or humiliate him. Guess what? A couple of days later, he told me that he did a Perl tutorial in his spare time, because he was sure it would save him lots of time and effort in the future. He never defended himself and he didn’t make lame excuses — he acted like a pro.

This is a guy you certainly want to hire! He possesses two traits that are much more valuable than knowledge: persistence and professionalism.

PROSPECTING FOR GOLD

To me, persistence and professionalism are not fundamental personality traits; I strongly believe that they’re the by-products of a root trait that I call “professional software passion” (PSP). Developers who possess a high degree of PSP are self-motivated and in general enthusiastic about their craft, they commit to life-long learning, are able to take a lot of hardship and always work towards fulfilling the business goals of their employers and clients — not just the short-term goals — especially the long-term goals.

Unfortunately, typical hiring processes completely ignore this critical trait. A certain level of intelligence and social skills is crucial, no doubt about it. Knowledge, however, can and will be obtained as long as PSP exists in a developer. PSP ensures that the job gets done. I would pick PSP over knowledge any day.

I will explore the topic of “professional software passion” as well as strategies on how to detect it in candidates in future posts. Stay tuned.