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# CAID-tools
Depi is a software-suite for tracking dependencies from across different types of tools and storages. At the core is the depi-server which provides a protocol for viewing and, adding and linking resources, reporting in updates in resources, etc. For the different supported tools there are user-interfaces (here implemented as vscode-extensions) and adapter/monitors that report in updates to the resources. The currently supported tools are `git`, `git-gsn` and `webgme`.
The CAID-tools are a software-suite for tracking dependencies across different types of tools and storages. At the core is the depi-server which provides a protocol for viewing, adding and linking resources, reporting in updates in resources, etc. For the different supported tools there are user-interfaces (here implemented as vscode-extensions) and adapter/monitors that report in updates to the resources. The currently supported tools are `git`, `git-gsn` and `webgme`.
TODO: Reword this.
TODO: Reword the following:
In Depi, these different types of artifacts or _Resources_ are referred to as _Tools_, here `webgme`, `git` and `git-gsn`. A _Tool_ needs to the very least provide an interface for adding new _Resources_ (linking them can be done via the Depi Blackboard UI) and a mechanism for reporting in updates in the _Resources_. An actual collection of _Resources_ from a _Tool_ is referred to as _Resource-Group_. In the case of `git` a _Resource-Group_ is a specific repository and the _Resources_ are either files or directories within that repository.
| webgme | A WebGME project at a specific WebGME server instance | Model | webgme-monitor (webgme storage events) | [WebGME Client](vscode:extension/vu-isis.webgme-depi) |
| webgme | A WebGME project at a WebGME server instance | Model | webgme-monitor (webgme storage events) | [WebGME Client](vscode:extension/vu-isis.webgme-depi) |
## Repository structure
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Start out by cloning all the git-repositories that are part of this example. From the terminal in the bottom of the screen invoke the `clone_repos.sh` script.
This system consists of a system-model modelled in webgme (where models are stored in a mongo-database), source code used by the blocks in the system-model, a few git-repositories with either test-scripts or generated data. Finally there is an assurance model modelled in GSN Assurance that is also stored under git (in the `ansr` folder in the `gsn` repository). However from a perspective of Depi, those files are managed slightly different than regular git files where instead of being treated as regular files - the models are interpreted as Abstract Semantic Graphs.
This system consists of a system-model, modelled in webgme (where models are stored in a mongo-database), source code used by the blocks in the system-model, a few git-repositories with either test-scripts or generated data. Finally there is an assurance model modelled in GSN Assurance that is also stored under git (in the `ansr` folder in the `gsn` repository). However from a perspective of Depi, those files are managed slightly different than regular git files where instead of being treated as regular files - the models are interpreted as Abstract Semantic Graphs.
To view the current state of the example system press `Ctrl/Cmd + Shift + P` and start typing `Depi: Blackboard` and select the command. This will prompt you for a password to log into depi - the password for the `demo`-user is `123456`.
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This is where the example models live. These are a combination of states from:
- git repositories with source code and gsn-assurance models (see `./repos`)
- system models from webgme in the form of exported mongo documents (`./webgme`)
- finally an exported snapshot of the depi data-base itself (`./depi`) which groups and links the resources together
- finally an exported snapshot of the depi data-base itself (`./depi`) which groups and links the resources from the other tools together
## Building Running the Example Models
In addition to the models this repostiory also contains the neccessary resources for building and/or running the example system using docker. If you are new to these tools and want to try out them quickly we recommend using the monolithic docker-images exaplined and referenced in the root of this repository. (Note that the utilities for building those images and the models states reside here.)
## Building and Running the Example Models
In addition to the models this repository also contains the neccessary resources for building and/or running the example system using docker. If you are new to these tools and want to try out them quickly we recommend using the monolithic docker-images exaplined and referenced in the root of this repository. (Note that the utilities for building those images and the models states reside here.)
If you are further along and are considering hosting some of the services from this example and maybe integrate some of your own services (e.g. existing repositories at gitlab or github) - the `docker-compose.yml` is a good start. Below follows the steps needs to run it and initiate it with the state mentioned above.
