Behind the Scenes of Add-In Discovery in the Orcas System.AddIn [Jesse Kaplan]
Details about the System.AddIn’s Implementation of Add-In Discovery
Last time we discussed several common approaches to add-in discovery and some of the pros and cons of each. We reviewed type hierarchy, custom attribute, and xml manifest based discovery systems and primarily evaluated them on three high level criteria: development complexity, performance, and add-in developer experience. This time I’d like to go into the details on what we developed and how it builds on the lessons we learned while evaluating previous solutions.
We had two high level goals in mind when we developed our discovery system: minimize complexity for the add-in developer and make the solution fast enough to be used at runtime. We wanted the add-in developer experience to be as close to “inherit from an abstract base class and run with it” as possible and we wanted hosts to be able to use the UI thread to discover add-ins.
Fundamentally the system we developed is mostly based on the custom attribute approach but with intelligent caching and updating that lets you avoid doing the work at runtime. We tried to capture the add-in developer experience of the custom attribute solutions with the performance of the manifest based approach.
At development time the add-in developers experience is as simple as with the custom attribute model: they inherit from the right abstract base class, apply the AddInAttribute, and then start writing the add-in.
As we noted earlier however, the custom attribute based approaches have the downside that computing this information requires loading and examining a bunch of assemblies and are too slow to do on application start up or on the UI thread. With this in mind we went a step further and built a system that caches this information to disk. This also led us to split our discovery into two phases: Update and Find.
IList<AddInToken> tokens =
The update phase is where we do the work to examine the add-in directory and build the store (or cache) of all the add-ins available there. For each sub directory at the provided path we look at each dll in the directory looking for a type that has [AddInAttribute] applied to it and record the information in the attribute and the base class of the add-in and store all the found information in a file called AddIns.store in the directory provided. One thing to note here is that we examine all of these assemblies in a different AppDomain and we use ReflectionOnly loading: this ensures that the add-in code is never executed until it is activated and that a call to update does not pollute the hosts AppDomain with these assemblies. Rather than recomputing all this information at each call to update we examine the timestamps of the various items in this directory and compare it to the existing store file (if there is one) and decide whether or not there is anything new we need to look at and if not we return quickly.
In addition to providing an update method that does this work we also ship the command tool AddInUtil.exe with the framework that was designed to be called with a custom action in an installer or via a build script.
By providing both a runtime Update method and the command line tool we leave an important decision up to the host: the host can choose to call AddInStore.Update from within the host app and thus make the add-in deployment experience truly an x-copy one, or it can require that add-ins run the tool themselves as part of their setup. In addition we’ve also ensured that the store file itself is x-copyable along with the add-in directory and so if, for example, a host ships with a few add-ins pre-installed it can build the store file when it’s building its setup and just deploy that store file along with the add-ins.
In FindAddIns the host passes us the type it wants to use to talk to the add-ins, the directory it wants us to look in and it receives back a collection of AddInTokens representing all the add-ins we found that can be used through the provided abstract base class. This method was designed to be usable during application startup and on the UI thread and we go out of our way to make sure that no types are ever loaded during this call and that the only files we read are the store files at the specified location. If no one (either the host or the add-in) performed an update on that location then no add-ins will be found. Another interesting thing we do is that we keep the store file in memory so that subsequent calls to FindAddIns on the same directory will not require us loading the file again: we simply check to see if the file has been updated since we last loaded it from disk and only reload it if necessary.
The AddInToken objects returned from a FindAddIns call are the objects that the host can actually activate to get back an instance of the add-in. They also contain metadata about the add-in that the host can use to decide which add-ins it wants to load: the add-in always provides a friendly name for itself and can optionally specify a version, publisher, and a short description. All of this information was originally recorded by examining, but not loading, activating, or executing, the add-in during the Update call and was stored in the token object during FindAddIns: this means that the host can get specific information about the add-ins and make informed decisions about which ones to activate without having to every execute any add-in code.
Putting it Together
Let’s start with reviewing our three high level goals:
· Minimize complexity of the add-in developer
· Performance of discovery code at runtime
· Ease of host development
Fundamentally all an add-in developer has to do with our system is to inherit from the right abstract base class, apply the [AddInAttribute] to the add-in, and then copy the add-in to the directory the host looks. This was our pri-1 requirement and we’ve made sure that it’s just about as low overhead on the add-in developer as possible.
As far as performance is concerned we leave it up to the host to decide what is most important: can it handle the cost of updating the stores at runtime when new add-ins are installed and reduce the complexity of add-in deployment, or is it acceptable to require a custom action in the installer. If the add-in deployment is responsible for updating the store then our solution is faster than the xml based discovery – since we only need to look at one file and we don’t have to load an xml parser to do so – and if the host decides to do runtime Update then it only pays the cost of discovery when new things are installed and we handle caching that information to disk for future look ups.
Finally we come to the ease of host development and here we may have the best story of all: while our solution may be harder to develop than the solutions we reviewed last time, we’ve removed this complexity since will be shipping as part of the framework.
We really do let you install and find add-ins in two lines of code:
IList<AddInToken> tokens =
At the beginning of the last article I mentioned some exotic discovery mechanisms such as in a database, embedded in a document, and over RSS. We’re actually working with partners who are building these mechanisms on top of our discovery system and down the line we’ll have a series of blog posts demonstrating some of these techniques.
In our next behind the scenes post we’ll pull back the curtains on the magical third line of code that activates your add-ins: