What do people mean when they say (and write) lifecycle testing? - testing

I've been with my current company for about four months now and I've noticed how several of our RnD scopes/documents use the term "lifecycle testing."
I've always thought that this term would mean the entire testing phase of a project, but the context of the term suggests that it instead is when the software is tested with "live" or "real" data in a staging environment as close to the production environment as possible.
This has led me to wonder if I have misunderstood the meaning of the phrase, in which case, can somebody explain what lifecycle testing is supposed to be or mean?

A lifecycle of software is it's behaviour in the following situations:
Startup. Does it load correctly? Is it fast at startup? (Depends on what kind of software)
Mid-life. Does it use much memory? Does it clean up memory? Does it do what it's ought to do?
Exeting. Does it cleanup resources correctly? Does it closes everything down well?
Lifecycle testing is very important for server applications, where it's especially focussed on "mid-life" (it's not an official term btw). Server apps may never crash while doing something importantly, and if they do: they shouldn't bring down the complete system.
The clue "lifetime" of being "live" or "real" isn't much true, it's more being "alive" than "live".
For instance; I've build a Flash client-application which is a "billboard" application, displayed at a large screen, and I am lifecycle-testing it:
Graphics, does everything show up well? Not just the first minutes, but even 12 hours without restarting the app.
Auto-update, does that work?
etc.

Related

How does Smalltalk image handle IO?

I just started to learn Smalltalk, went through its syntax, but hasn't done any real coding with it. While reading some introductory articles and some SO questions like:
What gives Smalltalk the ability to do image persistence, and why
can't languages like Ruby/Python serialize
themselves?
What is a Smalltalk “image”?
One question always comes into my mind: How does Smalltalk image handle IO?
A smalltalk program can resume from where it exits, using information stored in the image. Say I have some opened TCP connections(not to mention all sorts of buffer), how do they get recovered? There seems to be no way other than reopening them(confirmed by this answer). And if Smalltalk does reopen those connections, isn't it going against the idea of "resume execution of the program at a later time exactly from where you left off"? Or is there some magic behind it?
I don't mind if the answer is specific to certain dialects, say Pharo.
Also would be interested to know some resources to learn more about this topic.
As you have noted some resources are not part of the memory heap and therefore will not be recovered just by loading the image back in memory. In particular this applies to all kinds of resources managed by the operating system, and cross-platform Smalltalks where you can copy the image from one OS to another and restart the image even have to restore such resources differently than they were before.
The trick in the Smalltalks I have seen is that all classes receive a message immediately after the image resumed. By implementing a method for that message they can restore any transient resources (sockets, connections, foreign handles, ...) that their instances might need. To find all instances some Smalltalks provide messages such as allInstances, or you must maintain a registry of the relevant objects yourself.
And if Smalltalk does reopen those connections, isn't it going against the idea of "resume execution of the program at a later time exactly from where you left off"?
From a user perspective, after that reinitialization and reallocation of resources, everything still looks like "exactly where you left off", even though some technical details have changed under the hood. Of course this won't be the case if it is impossible to restore the resources (no network, for example). Some limits cannot be overcome by Smalltalk magic.
How does the Smalltalk image handle IO?
To make that resumption described above possible, all external resources are wrapped and represented as some kind of Smalltalk object. The wrapper objects will be persisted in the image, although they will be disconnected from the outside world when Smalltalk is shut down. The wrappers can then restore the external resources after the image has been started up again.
It might be useful to add a small history lesson: Smalltalk was created in the 1970s at Xerox's Palo Alto Research Center (PARC). In the same time, at the same place, Personal Computing was invented. Also in the same time at the same place, the Ethernet was invented.
Smalltalk was a single integrated system, it was at the same time the IDE, the GUI, the shell, the kernel, the OS, even the microcode for the CPU was part of the Smalltalk System. Smalltalk didn't have to deal with non-Smalltalk resources from outside the image, because for all intents and purposes, there was no "outside". It was possible to re-create the exact machine state, since there wasn't really any boundary between the Virtual Machine and the machine. (Almost all the system was implemented in Smalltalk. There were only a couple of tiny bits of microcode, assembly, and Mesa. Even what we would consider device drivers nowadays were written in Smalltalk.)
There was no need to persist network connections to other computers, because nobody outside of a few labs had networks. Heck, almost no organization even had more than one computer. There was no need to interact with the host OS because Smalltalk machines didn't have an OS; Smalltalk was the OS. (You probably know the famous quote from Dan Ingalls' Design Principles Behind Smalltalk: "An operating system is a collection of things that don't fit into a language. There shouldn't be one.") Because Smalltalk was the OS, there was no need for a filesystem, all data was simply objects.
Smalltalk cannot control what is outside of Smalltalk. This is a general property that is not unique to Smalltalk. You can break encapsulation in Java by editing the compiled bytecode. You can break type-safety in Haskell by editing the compiled machine code. You can create a memory leak in Rust by editing the compiled machine code.
So, all the guarantees, features, and properties of Smalltalk are only available as long as you don't leave Smalltalk.
Here's an even simpler example that does not involve networking or moving the image to a different machine: open a file in the host filesystem. Suspend the image. Delete the file. Resume the image. There is no possible way to resume the image in the same state.
All Smalltalk can do, is approximate the state of external resources as good as it possibly can. It can attempt to re-open the file. If the file is gone, it can maybe attempt to create one with the same name. It can try to resume a network connection. If that fails, it can try to re-establish the connection, create a new connection to the same address.
But ultimately, everything outside the image is outside of the control of Smalltalk, and there is nothing Smalltalk can do about it.
Note that this impedance mismatch between the inside of the image and the "outside world" is one of the major criticisms that is typically leveled at Smalltalk. And if you look at Smalltalk systems that try to integrate deeply with the outside world, they often have to compromise. E.g. GNU Smalltalk, which is specifically designed to integrate deeply into a Unix system, actually gives up on the image and persistence.
I'll add one more angle to the nice answers of Joerg and JayK.
What is important to understand is the context of the time and age Smalltalk was created. (Joerg already pointed out important aspect of everything being Smalltalk). We are talking about time right after ARPANET.
I think they were not expecting the collaboration and interconnection we have nowadays. The image was meant as a record of a session of a single programmer without any external communication. Times changed and now you naturally ask the IO question. As JayK noted you can re-init the image so you will get image similar to the point you ended your session.
The real issue, the reason I've decided to add my 2c, is the collaboration among multiple developers. This is where the image, the original idea, is, in my opinion, outlived. There is no way to share an image among multiple developers so they could develop at the same time and share the code.
Imagine wouldn't it be great if you could have one central image and the developers would have only diffs and open their environment where they ended with everyone's new code incorporated? Sound familiar? This is kind of VCS we have like mercurial, git etc. without the image, only code. Sadly, to say such image re-construction does not exist.
Smalltalk is trying to catch up with the std. versioning tooling we use nowadays.
(Side note: Smalltalk had their own "versioning" systems but they rather lack in many ways compared to the current VCS. The ones used Monticello (Pharo), ENVY (VA Smalltalk), and Store (VisualWorks).)
Pharo is now trying to catch the train and implement the git functionality via iceberg. The Smalltalk/X-jv branch has integrated decent mercurial support. The Squeak has Squot for git (for now) [thank you #JayK].
Now "only" (that is BIG only) to add support for central/diff images :).
For some practical code dealing with image startUp and shutDown, take a look at the class side of ZnServer. SessionManager is the class providing all the functionality you need to deal with giving up system resources on shutdown and re-aquiring them again on startup.
Need to chime in on the source control discussion a bit.
The solution I have seen with VS(E)/VA is that you work with Envy/PVCS and share this repository with the developers.
Every developer has his/her own image with all the pros and cons of images.
One company I was working for was discussing whether it wouldnt make sense to build up the development image egain from scratch every couple of weeks in order to get rid of everything that might dilute the code quality (open Filehandles, global variables, pool dictionary entries, you name it, you will get it and it will crash your code during run-time).
When it comes to building a "run-time", you take the plain tiny standard image, and all your code comes from bind files and SLLs.

I want a sandboxed test environment that is *always* an exact copy of Production

I'm having an issue with a web application I am responsible for maintaining.
The system experiences regular bugs, and our support vendors are always asking us to see if we can "replicate the error in UAT". This is obviously a reasonable request. A lot of the time, for various reasons (some of which are clear, some of which are not), these errors are not present in UAT. This lack of bug reproducability in a testing environment is adding huge amounts of friction to the bug resolution process.
There are 3 key pieces of our system architecture where these bugs are flaring (the CMS, the API layer, and the database). I am proposing we set up a system job that perpetually clones these 3 parts of the system in to a sandboxed test environment. This cloning would happen periodically (eg, once every 24 hours), and automatically.
Is there a technical term for this sort of environment? Is this an established method of helping diagnose system issues? Is there somewhere I can read up on the industry best practices for establishing something like this? Thanks.
The technical term for this kind of process is replication it is often done for some systems like databases, but normally not for testing purpose, but in order to increase available, so the replication is used as a failover spare.
An exact copy of a production system, with all the data is not you'll find often, due to the high demand on resources. Also at some points to two systems have to differ. Most systems (I know of) have tons of interfaces you just can't copy a complete system systems.
Also: you only need the copy of the production system when you actually debugging an issue. And if you are in the middle of that you probably don't want everything to go away and get replaced by a new copy.
So instead I would recommend to setup scripts that allows to obtain a copy of the relevant parts on demand.
Also you might want to consider how you might be able to modify your system to make it easier to setup a copy.
For example, when you have all the setup automated (with chef/docker or similar) you should be able to setup the same system again anywhere you want, so you now you just have to get the production data over.
Which is an interesting point. Production data often contains secret information (because it is vital to the business, or because it is personal data). You don't want this kind of stuff hang around in a test system everybody can access.

CEF3 single process mode in production

Are there any real pitfalls in using single process mode in production? The official statement seems to discourage this, but so far the application has been stable. CEF1 seems to have been abandoned, and if CEF3 single process is used for dev, then the latter should be at the very least be part of the test suite, and therefore stable. Or is that not true?
Also, is CEF3 single process not equivalent to CEF1? The new Battle.net launcher is using CEFl (1453). I wonder if that was for legacy reasons or if that was a conscious decision to avoid using CEF3.
This question is repeated often on cef's forum. The short answer is "don't take this path".
There are, from time to time, certain bugs that pops up on the single process mode and the official word from cef's maintainer is that this mode is unsupported, period. I think this is worded too lightly on the documentation, though.
People coming from cef1 background tends to keep doing it the old way, so single process mode seems like a good way to go, but the newer (now years old) cef3 highly depends on chromium's internals, and these are solely based on multiple process for production.

Why use AMQP/ZeroMQ/RabbitMQ

as opposed to writing your own library.
We're working on a project here that will be a self-dividing server pool, if one section grows too heavy, the manager would divide it and put it on another machine as a separate process. It would also alert all connected clients this affects to connect to the new server.
I am curious about using ZeroMQ for inter-server and inter-process communication. My partner would prefer to roll his own. I'm looking to the community to answer this question.
I'm a fairly novice programmer myself and just learned about messaging queues. As i've googled and read, it seems everyone is using messaging queues for all sorts of things, but why? What makes them better than writing your own library? Why are they so common and why are there so many?
what makes them better than writing your own library?
When rolling out the first version of your app, probably nothing: your needs are well defined and you will develop a messaging system that will fit your needs: small feature list, small source code etc.
Those tools are very useful after the first release, when you actually have to extend your application and add more features to it.
Let me give you a few use cases:
your app will have to talk to a big endian machine (sparc/powerpc) from a little endian machine (x86, intel/amd). Your messaging system had some endian ordering assumption: go and fix it
you designed your app so it is not a binary protocol/messaging system and now it is very slow because you spend most of your time parsing it (the number of messages increased and parsing became a bottleneck): adapt it so it can transport binary/fixed encoding
at the beginning you had 3 machine inside a lan, no noticeable delays everything gets to every machine. your client/boss/pointy-haired-devil-boss shows up and tell you that you will install the app on WAN you do not manage - and then you start having connection failures, bad latency etc. you need to store message and retry sending them later on: go back to the code and plug this stuff in (and enjoy)
messages sent need to have replies, but not all of them: you send some parameters in and expect a spreadsheet as a result instead of just sending and acknowledges, go back to code and plug this stuff in (and enjoy.)
some messages are critical and there reception/sending needs proper backup/persistence/. Why you ask ? auditing purposes
And many other use cases that I forgot ...
You can implement it yourself, but do not spend much time doing so: you will probably replace it later on anyway.
That's very much like asking: why use a database when you can write your own?
The answer is that using a tool that has been around for a while and is well understood in lots of different use cases, pays off more and more over time and as your requirements evolve. This is especially true if more than one developer is involved in a project. Do you want to become support staff for a queueing system if you change to a new project? Using a tool prevents that from happening. It becomes someone else's problem.
Case in point: persistence. Writing a tool to store one message on disk is easy. Writing a persistor that scales and performs well and stably, in many different use cases, and is manageable, and cheap to support, is hard. If you want to see someone complaining about how hard it is then look at this: http://www.lshift.net/blog/2009/12/07/rabbitmq-at-the-skills-matter-functional-programming-exchange
Anyway, I hope this helps. By all means write your own tool. Many many people have done so. Whatever solves your problem, is good.
I'm considering using ZeroMQ myself - hence I stumbled across this question.
Let's assume for the moment that you have the ability to implement a message queuing system that meets all of your requirements. Why would you adopt ZeroMQ (or other third party library) over the roll-your-own approach? Simple - cost.
Let's assume for a moment that ZeroMQ already meets all of your requirements. All that needs to be done is integrating it into your build, read some doco and then start using it. That's got to be far less effort than rolling your own. Plus, the maintenance burden has been shifted to another company. Since ZeroMQ is free, it's like you've just grown your development team to include (part of) the ZeroMQ team.
If you ran a Software Development business, then I think that you would balance the cost/risk of using third party libraries against rolling your own, and in this case, using ZeroMQ would win hands down.
Perhaps you (or rather, your partner) suffer, as so many developers do, from the "Not Invented Here" syndrome? If so, adjust your attitude and reassess the use of ZeroMQ. Personally, I much prefer the benefits of Proudly Found Elsewhere attitude. I'm hoping I can proud of finding ZeroMQ... time will tell.
EDIT: I came across this video from the ZeroMQ developers that talks about why you should use ZeroMQ.
what makes them better than writing your own library?
Message queuing systems are transactional, which is conceptually easy to use as a client, but hard to get right as an implementor, especially considering persistent queues. You might think you can get away with writing a quick messaging library, but without transactions and persistence, you'd not have the full benefits of a messaging system.
Persistence in this context means that the messaging middleware keeps unhandled messages in permanent storage (on disk) in case the server goes down; after a restart, the messages can be handled and no retransmit is necessary (the sender does not even know there was a problem). Transactional means that you can read messages from different queues and write messages to different queues in a transactional manner, meaning that either all reads and writes succeed or (if one or more fail) none succeeds. This is not really much different from the transactionality known from interfacing with databases and has the same benefits (it simplifies error handling; without transactions, you would have to assure that each individual read/write succeeds, and if one or more fail, you have to roll back those changes that did succeed).
Before writing your own library, read the 0MQ Guide here: http://zguide.zeromq.org/page:all
Chances are that you will either decide to install RabbitMQ, or else you will make your library on top of ZeroMQ since they have already done all the hard parts.
If you have a little time give it a try and roll out your own implemntation! The learnings of this excercise will convince you about the wisdom of using an already tested library.

What methods do you use to test for scalability in web applications?

Our testing system is pretty rudimentary; fire up a browser, see if it works. Recently we ran into problems, found by our client, with our application where the number of users created a slow-down in the application. The application is basically a huge Word document with people editing their own versions all at the same time. Part of the problem came from not knowing how to test multiple instances at the same time. My partner and I thought about how to test this; one idea was to hire out an internet cafe and hire students for an hour to bang on the app.
What are other ways that people have tried to emulate concurrency in testing their web-based application? Most of the advice here is for specific methodology; I'm asking, how do you test it to make sure that it works?
If you have never checked out Selenium, then you need to. It will allow you to do automated web testing through the browser. Ok, so first problem solved.
Now ideally you could use that same script and load it up on a bunch of boxes and run them all at once to get some sort of load testing right? Luckily for you someone has already figured this out, although it is a paid service: Browser Mob. But, it looks like you were willing to spend a little money to do this anyway, and would probably net you better, more repeatable results.
We usually answer the question "can the web application do more than one thing at a time" by using JMeter to produce a simulated HTTP load on the web server.
I find that it helps to consider distinguish several different types of testing; concurrency (what happens when two events in the system collide), capacity (what happens when there are many overlapping requests), volume (what happens as data accumulates in the system)...
Huge general slow down, evidenced by response times that fall outside of the SLA, are usually related to capacity problems (with contention as a common cause) or volume (many users, much data, and the system gets slower over time). The former usually requires some sort of multi-threaded request stream; the latter you can usually manage by preloading the volume, and then measuring the response times experienced by a single user.
I generally find that separating the load generator from the actual measurement/instrumentation is a good idea. That can be as simple as having a black box over there to generate a typical load, and sitting here with a stop watch measuring the responsiveness of a typical use case.
JMeter http://jmeter.apache.org/