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When dealing with software, stuff — be it technical or human — quite inexorably go wrong at some point for a variety of reasons. Here is a ‘memo’ list of shit that I lived or witnessed and hopefully ways to prevent them. Some points might look totally obvious but as I experienced them at least once they are probably worth listing.

This is not intended to be a list of technical difficulties encountered during the development phase but a reminder of what to think about before starting to code:

  • specifications: what is the role for the code/people in the project?
  • responsibility: what are the edge cases/possible input data that should be expected and how should they be handled?
  • quality: how can we measure the ‘success’ of the code?

as well as a list of possibly overlooked language fallacies/corner cases. Also we often only think in terms of code but organizational debt is just as real as the technical debt however it seems to be often more neglected; people more easily think in terms of a product instead of a team building a product.


Explicit is better than implicit

The Zen of Python


  • use shellcheck.
  • when processing unknown inputs in bash, you always end up with a filename containing a space. Or worse. When manipulating a path or a string variable in bash, always use double quotes unless you’re 100% sure it will always work correctly.
  • there is no exception mechanism in bash. Every command or function has a return status telling if it was successful (0) or not (>0). Every command. It is very easy to forget to test an important status code e.g. with some piped commands. Bash has a special flag to prevent silent failures: set -e, which may be used either globally (e.g. by using #!/bin/bash -e shebang) or on a specific bloc of code i.e.

set -e
command0 | command 1
set +e
  • bash script often involve filesystem; even though the kernel only handles bytes, it may easily be overlooked that the locale may have an impact on file manipulations; e.g. 7z uses the locale when handling archives.


  • some STL functions require the definition of a strict weak ordering which means that x op y and y op x can not be true at the same time (especially x op x must be false). As the function signature does not impose anything more than taking two instances and returning a boolean, there is no way the compiler could detect that the function is not properly defined.
  • when using pointer wrappers, make sure you actually test the pointer value rather than the wrapper.
  • when ‘using’ namespace, you might not be aware of what version of a function you actually call. Do not use using namespace foo (especially since the compiler prefers overloaded function over template function which could result in the not expected function being called)


  • never trust user data:
    • safely decode incoming text (you will have non-UTF8 encodings somewhere so you have to understand encodings)
    • escape data (you will face code injection at some point)
  • never trust “external” data:
    • data may be partly missing
    • data may be malformed

    so make sure to clean it before using it.

  • if your product rely on a custom data format, this format will very likely evolve with time. By the time you make the format change, you will either have to be able to reprocess old data or otherwise increase the legacy burden. Think about being future-proof early.

Development environment

  • user rights and privileges are well known; however, in a rush (or not) it is very easy to forget this and perform some server changes while being logged as root that will break part of a service (typically ran as www-data). Never log as root.
  • not using a common environment locally and in production may cause undetected bugs e.g. the setup uses some bash script with non-POSIX commands, either the command themselves or some options might slightly change between two distinct environments (e.g. sort has a --random-sort option on Linux but not on OSX). Use a VM or a container to make sure there are no discrepancies between your environments.
  • when developing new features, we often purely rely on a local setup. This is fine however it will mask lots of ‘real usage’ issues. For example, uploading a file locally will likely be instantaneous but will take much longer on a distant server. Not considering this could lead to unusable code (e.g. synchronous upload that could freeze the whole system). Make sure to test features with a real setup early enough.
  • a lot of products somehow rely on files. You should know your filesystem. NFS typically needs to be fine configured depending on your usage requirements.

Failures & exceptions

  • when bootstrapping a project, it’s tempting to think that it should fail safe and not crash to give an impression of robustness to early users. This is probably ok for early development but will soon enough mask bugs. Don’t “catch all exceptions” everywhere, let the code crash, monitor, understand the real issues and then fix.


  • mathematical functions have a domain of definition; e.g. the C++ std::acos function will return NaN outside [-1; 1]. Make sure you know this and you control values sent to those functions.
  • depending on serialization format, exceptional values like NaN and ±inf may not be supported.
  • floats repartition is irregular (and, in spite of IEEE-754, numerical behaviors may depend a lot on your platform) and if you don’t take that into account, expect unexpected behaviors.


  • most image operations (e.g. resizing) should be performed in a linear space; you need to know in which colorspace are the pixels expressed (most probably sRGB)
  • transparency in an image should always be expressed in a linear space and should be premultiplied against colors to avoid nasty border effects (1, 2).


  • everything is an object in Python. Even if small integer values like 0 or 1 will usually return the same object, this is implementation dependant; see “investigating Python wats” for more details. Do not use is to test equality if objects are not singleton, always use ==.
  • in Python, functions are first class citizens and default values are stored in the func_default (__defaults__ in Python3) tuple attribute. Using a mutable object (e.g. a list or a dict) is probably one of the most common gotcha that will often cause unexpected results as the default value is being reused across distinct calls. Typically use None and assign the desired default value in the function body.
  • when working with filenames, Python os.listdir will behave differently when called with a unicode string or a 8-bit string:

    If you pass a Unicode string as the path, filenames will be decoded using the filesystem’s encoding and a list of Unicode strings will be returned, while passing an 8-bit path will return the 8-bit versions of the filenames.

    You should therefore always know what type of string you are currently using and if it is the proper type for what you want to do.

  • assert is useful ‘debug’ statement allowing to check that everything is going as expected in a program. This can be useful during a data migration to assert that the data being migrated has been correctly processed and the statement takes a second parameter to provide a human readable message. The gotcha here would be to call assert like a function
>>> assert(False, 'this is false')
<stdin>:1: SyntaxWarning: assertion is always true, perhaps remove parentheses?

>>> assert False, 'this is false'
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AssertionError: this is false

Note that the REPL issues a warning when called with a tuple. However if the assert statement is in a module, you will not see this and if you do not test your script on ‘faulty’ data you may just think that everything went fine when the assertions were actually not testing anything. Always test code thoroughly (especially a data migration) and make sure that safeguards are actually safe.

Security & credentials

  • as most staff members will have extra privileges, there are a good target for account hijacking. You must enforce strong password/authentication policy for staff members, be it on your service or external services like code hosting.
  • when dealing with people’s money, be very careful. Double check & test everything. Implement a refund system soon enough to prevent angry users to spread a bad reputation about your service.
  • when handling sensitive data such as a token or payment information, make sure to never log messages with the data in plain text. It is easy to overlook logs and have a security hole.
  • when implementing a token based API, be very careful when you communicate about it. It is very easy to let your token unencrypted in some slides or video leaving everyone able to use your identity easily. And as staff members usually have extra privileges, this could be a big security issue.


What goes well without saying, goes even better when you say it.

Charles-Maurice Talleyrand


  • when refactoring or rewriting code, do not change every part of the system at once
    • chances are high that you will loose focus, e.g. to fix some production bugs or another priority will pop up or even you will take some vacations; by loosing focus you will likely ship bad code
    • putting large changes in production can be more difficult hence it could very well delay the new code going live
    • if things go wrong, you will likely have a harder time finding the root cause of evil

    Keeping some legacy code that works during a refactoring does not increase the technical debt; it just allows you to ship code in production more quickly and safely.

  • never think of crunch mode as a good option. Split important projects in small deliverable steps; if you fail to do so, you are the captain of a ship that is drifting. Ensure people stay focused on their targets. Eventually consider pressuring the staff to meet the deadline or move the deadline. If you ask more with less from your staff, compensate them in some way. This will make everyone know that crunch mode is not something considered normal in your company.
  • if people complain a lot on the tools or processes (or the lack of it), search for solutions. Being agile is about being able to adapt and make everyone in the company, from developers to product managers, work efficiently together. Simplify tool chains. Educate people about their tools. Automate tasks. Write hooks. Make people happy with their work environment.


  • trust. A manager should trust her subordinates to produce quality work. Subordinates should trust their manager will help everyone give her best. Trust is a bilateral relation that should produce code that is controlled (typically by a test suite and code reviews) to make everyone confident with it.
  • care. Listen to your staff and co-workers. If you want people to give their best, you need to know and detect if something looks wrong. Do not force people to speak but give them real opportunities to do so.
  • treat with equality what you consider boring and interesting subjects. Every business has some shitty tasks that need to be done. If you overlook or neglect those, people that perform them will eventually feel demotivated.
  • make people feel responsible for their code. “Eat your own dog food” and let people search production logs & metrics to follow the impact of their changes and make sure that they have not broken unexpected things. Knowing that they have an impact on the product will likely make people more involved and as a side effect make them more careful about code they and others write.
  • people’s performance is actually often dictated by their boss management. If you are a manager and have difficulties with one or more subordinates do not simply blame them. You are also failing. Either you failed recruiting the right person or (more likely) are failing at helping people meet what you expect from them:
    • listen to feedback
    • be analytical to find what is not working (possibly ask for an external opinion to make sure you are not biaised in your analysis)
    • make sure people understand your expectations and their mission
    • communicate as clearly as possible
  • beware of the team culture. Joking (aka trolling) about everything gives the impression that nothing really matters and will make people less willing to share ideas or ask for help. Team cohesion is very important and you need to make people feel like they belong rather than just fit.
  • http://steveblank.com/2015/05/19/organizational-debt-is-like-technical-debt-but-worse/