Major Release Syndrome: A Case for Chronological Versioning
Version numbers are a necessary evil. Users and programmers need them when something goes wrong. When you search for the bug on the web, you want to know if there is a newer version released, which contains a fix. That's it.
Marketing people need version numbers to generate excitement. These days they have switched to code words like Jelly Bean, Yosemite, and Trusty Tahr to make releases even more exciting. I think they are more confusing for users who are not "in the know", but I'm not a marketeer so don't listen to me.
As a programmer, I am concerned with two things: version numbers need to be sequential and easy to manage. Dates are god's solution to this problem. At Bivio, we've been using Chronological Versioning for 15 years, and it's always easy to know the answer to these three questions:
In order to make them a bit more digestible, we split the date and the time, e.g. 20150410.205405. Not much to say about it.
Many people believe that Semantic Versioning is the right approach to numbering releases. This approach supposedly avoids "dependency hell", because users can know which releases break backwards compatibility. To solve this problem, version numbers are clearly specified as follows:
For simple systems, this works just fine. The programmers know the system well enough to understand when a change is not backwards-compatible.
Semantic Versioning assumes that APIs must at times be incompatible. This need not be the case. Unix has had compatible APIs for decades.
You can then use the resultant program "shar" to recreate the shell archive from which it was built. The only change I had to make was to run make with "CFLAGS=-w" to turn off warnings, which did not exist in 1985, but the feature "make CFLAGS=-w" did exist in 1985.
Let's consider just how many APIs are 100% compatible three decades later:
Even better, the mail message sent by Perlman contains properly formed RFC 822 header lines (some were stripped by the archiver):
This message is 100% compatible with today's mail systems, and I sent it to gmail verbatim to see it worked:
Note that the text in the message: "Here is a new version of my C share program." No version number, but the shar does have a perfectly valid and understandable release identifier:
There are many other examples of maintaining compatibility over decades such as HTML, MS-DOS, Perl, Lisp, qwerty, etc. I think it is safe to say that the most successful systems out there are the ones which have taken great pains to be keep their APIs compatible over the years.
Chronological Versioning is in use on a few systems such as Ubuntu and CoreOS. Ubuntu 10.4 was released in April 2010. Ubuntu takes Chronological Versioning one step further by forcing releases to be time-based, that is, new release are promoted on a fixed schedule: 6 month releases with a long term support release every two years. In any given release, backwards compatibility will almost certainly break, because Ubuntu is far too complex to know if any one API is not backwards compatible.
Ubuntu's release promotion schedule avoids Major Release Syndrome, which is the idea that software is reliable if it is delivered in well-defined and completely understood chunks. This is the core philosophy behind Semantic Versioning, which works fine for simple systems. However, any sufficiently complex system such as Ubuntu are not knowable.
An Ubuntu release is a point in time snapshot in a stream of updates so no one really knows what version they are running. If you "apt-get" a package that wasn't previously on your system, your system has just been updated to a unique version of Ubuntu. Your computer is running a unique combination of packages installed at a specific time, which has its own unique set of bugs.
The folks at CoreOS take time-based releases one step further:
“CoreOS releases progress through each channel from Alpha → Beta →
Stable. You can think of each release on a lower channel as a release-candidate
for the next channel. Once a release is considered bug-free, it is promoted bit-for-bit
to the next channel.
There are no major releases with CoreOS. Users get to choose an update stream, and the releases flow after they are promoted to that stream (alpha, beta, or stable). Their update philosophy is simple: We believe that frequent, reliable updates are critical to good security.
What matters to the CoreOS team and their customers is release promotion, not version numbers. CoreOS has version numbers, but they are the same across alpha, beta, and stable channels, which means that you know that by the time a version is promoted to stable, it has gone through the alpha and beta channels.
With semantic versioning, alpha, beta, release candidates, and final versions all have different numbers. This usually means the promotion process involves recompiling the code. While this theoretically will produces exactly the same package as the previous release level, there's no guarantee that the underlying operating system hasn't been updated between compiles. A small bug fix might introduce an incompatibility between promotion levels. This is why CoreOS promotes the already compiled packages, not the source code.
Patches are Dangerous
Semantic versioning makes the assumption that patches are "better" in some sense than backwards-compatible features. I don't see it that way.
A backwards-compatible feature is new code. An API is less likely to break when someone is focusing on a new feature. Refactoring can break code, of course, but that can happen with any change.
Patches fix existing APIs. If anything is going to break an API, it's changing the code that underlies. Bugs are often caused by copy-and-paste errors so the proper patch is to refactor the code. To my mind, there's very little difference between a patch and feature, that is, if they are both coded to be backward compatible.
While backwards compatibility can be guaranteed, programmers want to take advantage of newer APIs for better security, faster performance, etc. We can take advantage of new APIs through two mechanisms: feature testing and shims.
Shims are easy to explain:
“A shim is a small library that transparently intercepts API calls and changes the arguments passed, handles the operation itself, or redirects the operation elsewhere. Shims typically come about when the behavior of an API changes, thereby causing compatibility issues for older applications which still rely on the older functionality. In such cases, the older API can still be supported by a thin compatibility layer on top of the newer code. Web polyfills are a related concept.”
Many programming languages have builtin shims. For example, you can use the "future" module in Python to make your code both forwards and backwards compatible.
An older feature is called "feature testing", which first came about to support software portability. The article Feature-Based Portability by Glenn S Fowler, David G Korn, J J Snyder, Kiem-Phong Vo, 1994 explains the problem quite clearly:
Version Testing is Evil
One of the biggest dangers of Semantic Versioning is that programmers will rely on a version number to ensure compatibility instead of using feature testing or shims. Version testing is using the version number to drive the way the software behaves. Here's an example from Writing Backward-Compatible Code: Appendix A - Ruby Best Practices by Gregory Brown:
Brown warns us to "Resist this temptation! If you aren't careful, this will result in a giant mess that will be difficult to refactor, and will make your code less readable. Instead, we can approach this in a more organized fashion."
Instead he recommends, Selective Backporting where he creates a shim as follows:
This encapsulation depends on the feature test for the "lines" method. It's clear what's going on, and keeps the code modular and maintainable. With version testing, there is an implicit coupling between the feature and the version number. If you happen to get the version number wrong, or worse, the feature changes yet again in another version, your code will break. It's much more reliable to test for feature existence.
This article does not have a version. It has an original release date (below) and with luck, I'll improve it over time. Nobody cares about those updates. If someone finds a bug in this article, they'll email me around the same time, and I'll know which version they are talking about. Nothing more is needed.
Semantic Versioning is much more complex. There are 11 clauses in the specification. Chronological Versioning is so simple that it needs only one rule: YYYYMMDD.HHMMSS. This numbering system complies with all build systems so it's plug and play.
Dependency hell is the driving force behind Semantic Versioning. Unfortunately, Semantic Versioning promotes the poor programming practice of not maintaining backwards compatibility and relying on version numbers for API changes.
These poor programming practices cause dependency hell, not the other way around. We have known how to make systems which survive API changes for decades. Well-written and (surprise!) popular software maintain backwards compatibility for this very reason. Feature tests and shims allow code to take advantage of newer APIs seamlessly. Version numbers are not required for either of these practices.
Versions are a necessary evil. Chronological versions allow us to manage releases as simply as possible.
Via Rob 04/11/15
Major Release Syndrome: A Case for Chronological VersioningSecurityTip: Deny by DefaultDigital Name Management: Own Your Name SpaceHow to Safely and Easily Manage PasswordsHow To Detect Phishing EmailsFacebook is a NOPServiceReview: InstacartBe Cheerful, Hopeful, GritfulDispatch, Don't DecorateVexillological Design LessonsLazy InvestingUS Government Cloud Computing Technology RoadmapBookReview: The Logic of Scientific DiscoveryBuild Identity Through Hard ChoicesBookReview: How to Fail at Almost Everything and Still Win Big: Kind of the Story of My LifePythonTip: "import from" Considered HarmfulBackpacking: Lost Creek WildernessNuclear Deterrence For Your CloudBookReview: Startup CEO: A Field Guide to Scaling Up Your
BusinessBookReview: The Structure of Scientific Revolutions (3rd Edition)The Psychology of Software TestingOwn VirtuallyBookReview: Fool's Gold: How the Bold Dream of a Small Tribe at J.P. Morgan Was Corrupted by Wall Street Greed and Unleashed a CatastropheBookReview: How to Be Alone: EssaysBookReview: Eat, Pray, Love▶ More▲ Most Recent
|back to top||© 2018 Rob Nagler||Software by bivio|