== How to Implement Parameter Catalogs with Eclipse
:imagesdir: ParameterCatalogs2Images

At the end of this chapter, you should be able to build a running software prototype for creating and maintaining parameter catalogs based on a graphical data model of the domain you are an expert in.

To build data models and parameter catalogs from scratch, we first have to understand some basics about Eclipse, and then install the correct Eclipse package.
Thereafter, we can model our data with _Ecore_ considering some best practices, followed by the generation of Java classes and user interface (UI).
Finally, we will install some plug-ins to "pimp" our Eclipse installation in order to add units and quantities to the mix.


=== Eclipse Basics

https://en.wikipedia.org/wiki/Eclipse_(software)[Eclipse] was originally developed by IBM and became Open Source in 2001.
It is best known for its Integrated Development Environments (_Eclipse IDEs_), not only for Java, but also for C++, Python and many other programming languages.
These IDEs are created on top of the Eclipse Rich Client Platform (Eclipse RCP), an application framework and plug-in system based on Java and OSGi.
Eclipse RCP is foundation of a plethora of general-purpose applications, too.

First time users of Eclipse better understand the following concepts.

.Eclipse Packages

An Eclipse package is an Eclipse distribution dedicated to a specific type of task.footnote:[The notion of an Eclipse package has nothing to do with Java packages.]
A list of packages is available at https://www.eclipse.org/downloads/packages/[eclipse.org].
Beside others it contains _Eclipse IDE for Java Developers_, _Eclipse IDE for Scientific Computing_, and _Eclipse Modeling Tools_.
Note that third parties offer many other packages, e.g. _GAMA_ for multi-agent-simulation.

[NOTE]
====
Several Eclipse packages can be installed side by side, even different releases of the same package. Multiple Eclipse installations can run at the same time, each on its own _workspace_ (see below).
====

.Plug-ins / Features

An installed Eclipse package consists of a runtime core and a bunch of additional plug-ins.
Technically, a plug-in is just a special kind of Java archive (JAR file) that uses and can be used by other plug-ins with regard to OSGi specifications.
Groups of plug-ins that belong together are called a _feature_.

Sometimes, a user will add plug-ins or features to an Eclipse installation to add new capabilities.
E.g. writing this documentation within my Eclipse IDE is facilitated by the plug-in https://marketplace.eclipse.org/content/asciidoctor-editor[Asciidoctor Editor].
Plug-ins can easily be installed via main menu command `Help → Eclipse Marketplace...` or `Help → Install New Software...`.
Some plug-ins may be self-made like our _City Units_ plug-in that enables Ecore to deal with physical quantities.

.Git

https://git-scm.com[Git] is the industry standard for collaborative work on, and versioning of, source code and other textual data.
Collaborative development of parameter catalogs benefits massively from using Git.
Git support is built into _Eclipse Modeling Tools_, the Eclipse package we will use.
However, if Eclipse needs to connect to a Git server that uses SSH protocol (not HTTPS with credentials), access configuration is more involved and may be dependent on your operating system.

Some users, anyway, prefer to use Git from the command line or with one of the client application listed https://git-scm.com/downloads/guis[here], e.g. https://tortoisegit.org[TortoiseGit] for Windows.

While it is required to get Git working at some point, we won't refer to it in this document and, for now, do not cover the installation of Git on your machine or configuration of Git in Eclipse.

.Workspaces

When you start a new Eclipse installation for the first time, you are asked to designate a new directory in your file system to store an _Eclipse workspace_.
Eclipse is always running with exact one workspace open.
As the name implies, a workspace stores everything needed in a given context of work, namely a set of related projects the user is working on as well as meta-data like preference settings, the current status of projects, to do lists, and more.
In case a user wants to work in different contexts, e.g. on different tasks, command `File -> Switch Workspace` allows to create additional workspaces and to switch between them.

[NOTE]
====
Any plug-in from the original Eclipse package or installed by the user later will be copied into the Eclipse installation directory, *not* in any workspace.
Configuration and current state of plug-ins, on the other hand, are stored in workspaces.
====

.Projects

An Eclipse project is a technical term for a directory that often contains:

* files of specific types for source code, scripts, XML files or other data
* build settings, configurations
* dependency definitions (remember the dependencies between plug-ins above?)
* other Eclipse projects.

`File -> New -> Project...` offers many different types of projects that the user can choose from, e.g. Java projects to create Java programs, Ecore modeling  projects, or general projects, that simple hold some arbitrary files.footnote:[Projects possess one or more _natures_ used to define a project's principal type.]

[WARNING]
====
Files that do not belong to a project are invisible for Eclipse!
====

The projects belonging to a workspace can either be directly stored within the workspace as sub-directories (the default offered to the user when creating a new project), or linked from it, that is the workspace just holds a link to the project directory that lives somewhere in the file system outside of the workspace.
Linking allows to work with the same projects in different workspaces.

While it sometimes makes sense to share or exchange workspaces between users,footnote:[Or even work on the same workspace provided in the cloud, see https://www.eclipse.org/che/technology/[Eclipse Che].], I do not recommend this for now.
Projects, in contrast, are shared between users most of the time, usually via Git.
In general, I would suggest to store Eclipse projects outside workspaces at dedicated locations in the user's file system.
That way, we can follow the convention that local Git repositories should all be located under 
`<userhome>/git`.


=== Setup Eclipse Modeling Tools

.[line-through]##Install Java##

Starting with version 2022-03 Eclipse packages come with a bundled Java Development Kit (JDK), version 17.
Thus, there is no need anymore to install a JDK manually.

.Install Eclipse Modeling Tools

Our graphical and form based modeling tools, e.g. Insel 9.0 and Parameter Catalogs, run on top of Eclipse Sirius, an open source framework that provides a set of features and plugins that can be added to any Eclipse package to transform it into a very flexible modeling workbench.

We will install Eclipse package _Eclipse Modeling Tools_ first and, then, Eclipse Sirius on top. To get current version 4.23 (2022‑03) of _Eclipse Modeling Tools_, go to https://www.eclipse.org/downloads/packages/[www.eclipse.org/downloads/packages/].
On this page you may see _"Try the Eclipse Installer"_ or similar.
Do *not* follow this advice, since we want more control over what will be installed.
Instead, look for package _Eclipse Modeling Tools_ and click the download link for your operating system and system architecture displayed on the right:

.Download links for Eclipse Modeling Tools package
image::EclipseModelingDownload.png[Eclipse Modeling Download, 500, role="thumb"]

Finally, click on `Download` and wait for the 550 something MB package to arrive.
On macOS this is a disk image file (.dmg) that is mounted by a double click. Drag and drop  `Eclipse` to folder _Applications_ and rename the copy to something more specific like `EclipseModeling2203`.

On windows and Linux unzip/extract the downloaded file and possibly rename the resulting application to `EclipseModeling2203` or similar. Then, move the application to a suited directory, but **not** `Programs` or `Programs (x86)` on Windows!

[WARNING]
====
**Special installation note for Windows**: We found that sometimes plug-ins cannot be added to Eclipse, **if** it is installed in folder _Programs_ or _Programs (x86)_. Since we have to add plug-ins for Sirius and for handling units and quantities below, please make sure to unzip the installation package elsewhere, e.g. the Desktop or the user's home directory.
====

[NOTE]
====
Depending on the operating system, several security dialogs have to be acknowledged during installation and first launch of Eclipse Modeling Tools.
====

After installation has finished, launch the application for the first time and you will see a dialog for choosing a new empty directory as its workspace.

.Initial Dialog to Choose a Workspace Directory
image::SelectWorkspaceDirectory.gif[SelectWorkspaceDirectory, 500, role="thumb"]

More workspaces might come into existence later, so replace the proposed generic directory path and name with a more specific one, e.g.`EclipseWSCatalogs`.
The main window appears with a Welcome Screen open.
Especially under `Workbench Basics` you will find exhaustive documentation on Eclipse that might be of interest later, e.g.:

** Workbench User Guide
*** Concepts: perspectives, projects, views, editors, features, resources, ...
*** Tasks: Working with perspectives, views and editors, installing new software. ...
** EGit Documentation
*** EGit User Guide
*** Git for Eclipse Users
** Ecore Tools User Manual: Learn how to design Ecore models.

For now, you can dismiss the welcome screen. It can be opened anytime by executing `Help -> Welcome`.

Now you should see the initial window layout with _Model Explorer_ and _Outline_ on the left and a big empty editing area to the right with a _Properties_ view below.


.Install Eclipse Sirius

While package _Eclipse Modeling Tools_ already contains Sirius features that let you create graphical Ecore models, features for specifying your own forms and graphical editors are still missing.
You can add these features easily with Eclipse's built-in update mechanism:

* Open dialog `Help -> Install New Software...` (see screenshot below)
* For _Work with:_ choose software site `2022-03 - https://download.eclipse.org/releases/2022-03/` 
* Deselect _Group items by category_
* Type _Sirius_ into the search field
* From the list of features select
** `Sirius Properties Views - Specifier Support`
** `Sirius Query API for AQL`
** `Sirius Specifier Environment`
** `Sirius Support for AQL` and click `Next >`
* Acknowlege any licenses and restart Eclipse when asked for.

.Install additional Sirius features
image::InstallSiriusSpecifier.png[Install Sirius Specifier, 500, role="thumb"]


[[quantity-plug-ins]]
.Add Plug-ins to deal with Quantities and Units

Now we use the same update mechanism to add software components that were created specifically for parameter catalogs and hosted at the transfer portal of _HfT Stuttgart_.

Parameter catalogs should be able to represent quantities, not just bare numbers.
See https://onlinelibrary.wiley.com/doi/full/10.1002/spe.2926[Unit of measurement libraries, their popularity and suitability] for a systematic account of open source solutions in the this area. 
Java provides an extensive framework to deal with quantities and their units defined in https://docs.google.com/document/d/12KhosAFriGCczBs6gwtJJDfg_QlANT92_lhxUWO2gCY/edit#heading=h.6698n7erex5o[Java Specification Request (JSR) 385].
The reference implementation for this framework is https://unitsofmeasurement.github.io/indriya/[Indriya]. Demos of its usage can be found at https://unitsofmeasurement.github.io/uom-demos/[].

While Indriya offers all common SI units and more, the author provided additional units specific to urban simulation plus specialized Ecore types for specifying these units for attributes in Ecore data models as an Eclipse feature named _City Units_.

The new types are named _Quantity_ and _TimeOfDay_.
Some examples of valid unit symbols are listed in this https://transfer.hft-stuttgart.de/gitlab/neqmodplus/de.hft-stuttgart.cityunits[README].

To install _City Units_, open dialog `Help -> Install New Software...` and enter site `https://transfer.hft-stuttgart.de/pages/neqmodplus/de.hft-stuttgart.cityunits/p2repo` like depicted below.

.Install Feature CityUnits from Update Site
image::InstallCityUnits.png[Install Plug-in, 500, role="thumb"]

Select _City Units_, press `Next >` and acknowledge all following dialogs, including security warnings.

Finally, restart Eclipse to complete installation.


=== Exercise: Modeling a Parameter Catalog with Ecore

Before we start working on real catalog projects hosted in a Git repository in the next section, let us first create a demo project for playing around and learning basic modeling skills.

[quote,Phil Karlton / N.N.]
____
There are two hard problems in computer science: cache invalidation, naming things, and off-by-1 errors.
____

It takes time and effort to come along with good names for model entities, projects, files, and so on.
Also, specific naming conventions are in place to enhance readability of models and program code.
Since it is not always clear where names provided during modeling are used later, I compiled a list of names important in Ecore projects and added examples and comments to elucidate their meaning and naming conventions.

.Naming
[width="100%",options="header"]
|====================
| Name             | Demo Catalog Example           | Real World Expample 
| Namespace URI    | http://example.org/democatalog | http://hft-stuttgart.de/buildingphysics 
| Namespace Prefix | democat                        | buildphys 
| Base Package (reverse domain)footnote:[https://en.wikipedia.org/wiki/Reverse_domain_name_notation]
                   | org.example                    | de.hftstuttgart 
| Main Package     | democatalog                    | buildingphysics 
| Eclipse Projectfootnote:[https://wiki.eclipse.org/Naming_Conventions#Eclipse_Workspace_Projects]
                   | org.example.democatalog.model  | de.hftstuttgart.buildingphysics
| Class Prefix     | Democatalog                    | Buildingphysics 
| XML File Suffix  | democatalog                    | buildingphysics 
| Classes          | e.g. SolarPanel                | e.g. WindowType 
| Attributes       | e.g. nominalPower              | e.g. id
| Associations     | e.g. solarPanels               | e.g. windowTypes 
|====================

Classes are written in https://en.wikipedia.org/wiki/Camel_case[Camel case notation] starting with an upper case letter. Associations and attributes are written the same way, but starting with a lower case letter.

All other names should be derived from the globally unique _name space_ of the project, in our example: `example.org/democatalog`.
It consists of a global unique domain name and a path to the project, unique within that domain.

Use the names of example _Demo Catalog_ to create your first Ecore modeling project:

. Execute `File -> New -> Ecore Modeling Project` from main menu -- not `Modeling Project`!
. Name the project `org.example.democatalog.model` and uncheck _Use default location_ so that the new project is *not* stored in workspace but a different directory you create/choose, then click `Next >`
. Provide `democatalog` as main Java package name, uncheck _Use default namespace parameter_ and provide `http://example.org/democatalog` as _Ns URI_ and `democat` as _Ns prefix_
. Click `Finish`.

Eclipse should look like below with an new empty graphical Ecore diagram editor opened.
The diagram is automatically named `democatalog` after the package name for the Java classes that will be generated from it (provided above).
The _Model Explorer_ shows the contents of the new Ecore modeling project.

[[fig-ecore-modeling-project]]
.New Ecore Modeling Project
image::DemoCatalogEmpty.png[DemoCatalogEmpty, role="thumb"]

To get your feet wet, do this:

. Drag a _Class_ from the palette on the right onto the editor's canvas: it will materialize as a rectangle labeled `NewEClass1`.
. The class symbol should be selected initially, so you can see its attributes in the _Properties_ view.
. In there replace `NewEClass1` by `EnergyComponentsCatalog` to rename the class.
. Click anywhere on the canvas and notice that the class symbol is deselected and the toolbar at the top adapts accordingly.
. In the toolbar change `100%` to `75%` to scale diagram.
. Execute `File -> Save` to save model and diagram on disk.
. Close diagram editor `democatalog` by closing its tab.
. Reopen saved diagram by double click on entry `democatalog` in _Model Explorer_. 

Technically, everything is in place now to begin modeling the data that the projected catalog shall contain.
Except ... understanding the basics of object-oriented modeling would be helpful.
This is why developers should support domain experts at this stage.


.Model Data with Class Diagrams

Ecore diagrams are simplified UML class diagrams.
Here some resources on what this is all about:

* http://www.cs.toronto.edu/~sme/CSC340F/slides/11-objects.pdf[Toronto Lecture on Object Oriented Modeling]
* http://agilemodeling.com/artifacts/classDiagram.htm[UML 2 Class Diagrams: An Agile Introduction]
* https://www.amazon.de/UML-Classroom-Einführung-objektorientierte-Modellierung-ebook/dp/B00AIBE1QA/ref=sr_1_2?__mk_de_DE=ÅMÅŽÕÑ&dchild=1&keywords=UML&qid=1585854599&sr=8-2[UML @ Classroom: Eine Einführung in die objektorientierte Modellierung (German Book)]

[TIP]
====
Beginners are strongly encouraged to read the first two resources.
The first one contains a gentle introduction, especially suited for domain experts.
The second one can also serve as reference.
====

We will touch central object-oriented concepts _Class_, _Object_, _Attribute_, _Association_, _Composition_, and _Multiplicity_ in an example below, but work through above sources to get a deeper understanding and to enhance your modeling skills.

Note that above sources differentiate between _conceptual_ and _detailed_ models.
We go for detailed models, since only these contain enough information to generate code.
Having said this, it is usually a good idea to have two or three conceptual iterations at a white board to agree on the broad approach before going too much into detail.
But even if one starts with Ecore models right away, these also can be adapted any time to follow a new train of thought.

See here the essential and typical structure of a parameter catalog in a class diagram.
Instead of artificial example classes like _Foo_ and _Bar_ it shows classes from an existing catalog, albeit in very condensed form.

.Principle Structure of a Parameter Catalog
[plantuml, CatalogStructure, png, role="thumb"]
----
together {
  class SolarPanel
  class Inverter
}

class EnergyComponentsCatalog {
    author: String
}

abstract class EnergyComponent {
    modelName: String
    revisionYear: int
}

abstract class ChemicalDevice {
    installedThermalPower: double
}

abstract class ElectricalDevice {
    nominalPower : double
}

class Boiler {
    type : BoilerType
}

class CombinedHeatPower {
    thermalEfficiency : double
    electricalEfficiency : double
}

class Manufacturer {
    name : String
}

enum BoilerType {
  LowTemperature
  Condensing
}

class SolarPanel {
    mppVoltage : double
    mppCurrent : double
}

class Inverter {
    maxDCVoltage : double
    maxDCCurrent : double
}

BoilerType -[hidden]- Boiler

ElectricalDevice --|> EnergyComponent
SolarPanel --|> ElectricalDevice
Inverter --|> ElectricalDevice
ChemicalDevice --|> EnergyComponent
Boiler --|> ChemicalDevice
CombinedHeatPower --|> ChemicalDevice

EnergyComponentsCatalog *-- "0..*" Inverter: inverters
EnergyComponentsCatalog *-- "0..*" SolarPanel: solarPanels
EnergyComponentsCatalog *-- "0..*" Boiler: boilers
EnergyComponentsCatalog *-- "0..*" CombinedHeatPower: chps
EnergyComponentsCatalog *-- "0..*" Manufacturer: manufacturers
EnergyComponent -up-> "1..1" Manufacturer: producedBy
----

The diagram models four types of technical components whose data shall be stored in the catalog, e.g. for parameterization of simulation models later: _Boiler_, _CombinedHeatPower_, _SolarPanel_, and _Inverter_.

The catalog itself is represented by class _EnergyComponentsCatalog_.
Unlike dozens, hundreds, or even thousands of objects to be cataloged -- Boilers, Inverters etc. -- there will be just exactly *one* catalog object in the data representing the catalog itself.
Its "singularity" is not visible in the class diagram, but an _Ecore_ convention requires that all objects must form a composition hierarchy with only one root object.

.Composition
If, in the domain, one object is composed of others, this is expressed by a special kind of association called _composition_.
Compositions are depicted as a link with a diamond shape attached to the containing object. In the _Boiler_ case said link translates to: The _EnergyComponentsCatalog_ contains -- or is composed of -- zero or more (`0..*`) boiler objects stored in a list named `boilers`.

[IMPORTANT]
====
Note that class names -- despite the fact that they model a set of similar objects -- are always written in _singular_!
Names for list-like associations and attributes usually are written in plural form.
====

.Inheritance
Besides composition of *objects*, the model above shows another, completely different, kind of hierarchy: the inheritance hierarchy between *classes*.
Whenever classes of objects share the same attributes or associations, we don't like to repeat ourselves by adding that attribute or relation to all classes again and again.
Instead, we add a _super class_ to define common attributes and associations and connect it to _sub classes_ that will automatically _inherit_ all the features of their super class.

In our example above, common to all four energy components are attributes `modelName` and `revisionYear`, thus these are modeled by class `EnergyComponent` that is directly or indirectly a super class of _Boiler_, _CombinedHeatPower_, _SolarPanel_, and _Inverter_.
Similar, _Boiler_ and _CombinedHeatPower_ share attribute `installedThermalPower` factored out by class _ChemicalDevice_.
_SolarPanel_ and _Inverter_ share attribute `nominalPower` modeled in abstract class _ElectricalDevice_.

.Associations
You probably noticed a fifth type of objects contained in the catalog, namely `Manufacturer` objects stored in list `manufactureres`.
How come? Ok, here is the story:

.Domain Expert Meets Developer
****
_Exp_: "`I'd like to store a component's manufacturer. Shall I add a String attribute `manufacturerName` to all classes like _Boiler_, _Inverter_ and so on to store the manufacturer's name?`"

_Dev_ shudders: "`Well, what do you mean by "... and so on"?`"

_Exp_: "`Basically, I mean all energy components.`"

_Dev_: "`Fine. We already have a class representing all those energy components, brilliantly named _EnergyComponent_. Thus, we can define `manfacturerName` there, following one of Developer's holy principles: "_DRY_ -- Don't repeat yourself!"
By the way: Is the name all you want to know about manufacturers?`"

_Exp_: "`Mhm, maybe we need to know if they are still in business ...`"

_Dev_: "`... or even since when they were out of business, if at all ...`"

_Exp_: "`... and the country or region they are active.`"

_Dev_: "`Ok, so it's not just the name -- we need a class `Manufacturer` to model all these information.`"

_Exp_ sighs.

_Dev_: "`Come on, its not that hard to add a class to our data model, isn't it?`"

_Exp_: "`Ok, but how can we express what components a manufacturer produces?`"

_Dev_: "`Wasn't it the other way around? I thought, you just wanted to know the manufacturer of a component?`"

_Exp_: "`What is the difference?`"

_Dev_: "`In data modeling, it is the difference between a uni-directional and a bi-directional association.`"

_Exp_: "`...?`"

_Dev_: "`Let's put it that way: The difference between a link with an arrow on one side or on both sides.`"

_Exp_: "`Ok. We don't need a list of components per manufacturer, but simply a reference from the component to its manufacturer.`"

_Dev_: "`Fine, then in Ecore please create a simple reference from class `EnergyComponent` to class `Manufacturer`, maybe named `producedBy`.`"

_Exp_: "`I will try this and get back to you.`"

_Dev_: "`Fine ... good meeting.`"
****

Observe in our data model, reference `producedBy` points _from_ `EnergyComponent` _to_ `Manufacturer` making it uni-directional reference.
One can simply query the manufacturer of a product, but not the other way around.
With a bi-directional reference both queries would be available.

Observe also the annotations `0..*` and `1..1` near class `Manufacturer`.
These are _multiplicities_ of associations: An `EnergyComponentsCatalog` contains zero, one, or many objects of class `Manufacturer` and an `EnergyComponent` must reference exactly one manufacturer -- not less, not more.

[.float-group]
--
.Ecore Relations
image::EcoreRelations.gif[EcoreRelations, 200, float="right", role="thumb"]

To recapitulate: Our example parameter catalog already exhibits all four types of relations provided by Ecore.
You find these in the Ecore editor's palette shown here.
To create a relation between a sub class and a super class use tool `SuperType`.
Use the other tools to create an association between classes, may it be a simple (uni-directional) reference, a bi-directional reference, or a composition.
--

.Attributes and Enumerations

Obviously, attributes are central in data modeling.
Create one by dragging it from the palette onto our one and only class so far: `EnergyComponentsCatalog`.
The class symbol will turn red to indicate an error.
Hover with the mouse pointer over the new attribute and a tooltip with a more or less helpful error message will appear.
Current error is caused by that no data type was set for the new attribute.
Data types for attributes can be integer or floating point numbers, strings, dates, booleans, and more.
To get rid of the error:

. If not already selected, select new attribute by clicking at it in the editor.
. In view _Properties_ find `EType` and click button `...` to see a quite long list of available data types.
. Choose `EString [java.lang:String]` from the list and the error is gone.

[.float-group]
--
.Class with Attribute
image::EcoreClassWithAttribute.png[EcoreClassWithAttribute, 200, float="right", role="thumb"]

Change the attribute's name to `author` and the class should look like shown here.

Most data types to choose from begin with letter *E* like in **E**core.
These are just Ecore enabled variants of the respective Java types, thus, choose EInt for an int, EFloat for a 32 bit floating point number, EDouble for a 64 bit one, and so on.

Ecore allows to introduce new data types.
We employ this feature later to enable data models with physical units and quantities.  
--

There exists one other means to define the values an attribute can take, namely enumerations of distinct literals. Take _Monday_, _Tuesday_, _Wednesday_, ... as a typical example for representing weekdays.
In our example data model you'll find one _Enumeration_ named `BoilerType` with values `LowTemperature` and `Condensing`.


.Homework

The next section deals with generation of Java code from data models. To have more to play with, please implement our example model in Ecore now.

[.float-group]
--
.Abstract Class
image::EcoreClassifier.png[EcoreClassifier, 200, float="right", role="thumb"]

To do this, there is one more thing to know about classes: the difference between ordinary classes and abstract classes.
'Ordinary class' doesn't sound nice, therefore, classes that are not abstract are called _concrete_ classes.
Our example diagram depicts abstract classes with letter *A* while concrete classes are labeled with *C*. You add abstract classes to a model with a special palette tool shown here.

The thing is: Objects can be created for concrete classes only!

In our example, it makes no sense to create an object from class _EnergyComponent_, because there is not such a thing like an energy component _per se_.
Therefore, this class is _abstract_.
It is true that an inverter _is_ an energy component, thus inheriting all its features, but it was _created_ as _Inverter_, not as _EnergyComponent_.

Super classes will be abstract most of the time.
So my advice is: Model a super class as abstract class unless you convince yourself that there exist real objects in the domain that belong to the super class but, at the same time, do not belong to any of its sub classes.
In the Ecore editor properties view, you can specify if a class is abstract or not, simply by toggling check box `Abstract`.
--

Two more tips and you are ready to rock and roll! -- At least with your homework.

[TIP]
====
An exhaustive user manual for Ecore diagram editor is available at `Help -> Welcome -> Documentation -> EcoreTools User Manual`.
====

[TIP]
====
If Ecore models get bigger, you may find it more convenient to work with a form based UI instead of, or in addition to, the diagram editor.
Open this kind of editor via command `Open With -> Ecore Editor` from the context menu over entry `democatalog.ecore` in the _Model Explorer_ view.
Note that Eclipse synchronizes different editors of the same content automatically.
====

That's it for the data modeling part. By now, your Ecore model should look like this:

.Example Model (Homework)
image::Homework.png[Homework, role="thumb"]


=== Making a Prototype Application to Create and Edit Data

In this section you will get a glimpse on how to create an application to create and edit data conforming to the Ecore data model of our demo parameters catalog.

Topics described here (and much more) are discussed in this https://wiki.eclipse.org/Sirius/Tutorials/StarterTutorial/[Sirius Starter Tutorial].

If you are less interested in the details of UI creation, but more in working on already existing parameter catalog software and data, you may skip this section for now and proceed with <<Working with Git Hosted Catalogs>>.


.Generation of Java Code from Data Model 

Let us bring the Ecore data model to life, that is, generate code from it that allows to create, read, update, and delete (CRUD) concrete data objects of modeled classes in computers:

. Make sure all files are saved (`File -> Save All`)
. Execute `Generate -> All` from the context menu of Ecore editor `democatalog`

[.float-group]
--
.Generated Classes
image::GeneratedClasses.png[GeneratedClasses, 260, float="right", role="thumb"]

`Generate -> All` creates classes that represent the modeled data in code at first. These classes are located in three packages under directory `src-gen` in `org.example.democatalog.model`. Then, the command generates `Edit Code` and `Editor Code` within two new Eclipse projects named `org.example.democatalog.edit` and `org.example.democatalog.editor`, again with generated classes in `src-gen`.

You may have a look at some Java classes for curiosity by double clicking at them in _Model Explorer_. There is no point in trying to understand the code in detail, but observe token `@generated` present in the comments of all classes, fields and methods. Classes, fields and methods marked with this token are (re)generated whenever above commands are executed.

Sometimes it is required to manually adapt generated code -- after all our concern is "low code", not "no code" development. In that case, we will replace `@generated` by `@generated NOT` to prevent code regeneration of the respective item.

After code generation, you may have noticed some warnings showed up in view _Problems_.

.Warnings
image::Warnings.gif[Warnings, 500, role="thumb"]

In general, it is highly recommended to resolve warnings, and errors of course, but we will make an exception from the rule, since the warnings are uncritical and would reappear each time code is regenerated.
--


.Create a Prototype Application for Data Editing and UI Design

Firstly, launch a new instance of the running _Eclipse_ application:

. Execute `Run -> Run Configurations...` from the main menu and double click on _Eclipse Application_ to get a _New_configuration_. You may want to rename _New_configuration_ to _DemoCatalog_ or the like.
. Press `Run` to start the new Eclipse application that is basically a copy of your running _Eclipse_ but with a different workspace.
. In the new application window close the welcome screen and open the Sirius perspective using the suited button in the top right corner of the main window. This perspective provides specific Sirius menus and new project types.

Secondly, create a project that will contain catalog data (remember Eclipse can only handle files that are part of a project):

. From main menu execute `File -> New -> Modeling Project` -- not `Ecore Modeling Project`!
. Name the project `org.example.democatalog.data` and uncheck _Use default location_ so that the new project -- again -- is *not* stored in workspace but a different directory you create/choose, usually a directory named like the project and sitting side by side to the model, edit and editor project directories created above.
. Click `Finish`.

Thirdly, create a first XML file for catalog data:

. From main menu execute `File -> New -> Other...` and type `demo` into search field _Wizards:_
. Select `Example EMF Model Creation Wizards -> DemoCatalog Model` and click `Next >`
. Select `org.example.democatalog.data` as parent directory and name the data file `First.democatalog`
. Click `Next >` and choose `Energy Component Catalog` as the root data object that will be created initially
. Click `Finish`.

A new entry named _First.democatalog_ should appear in the _Model Explorer_.
Double-click it and a *generic* editor will open.
In principle, one could use this editor to add new data to the catalog via `New Child >` in the context menu over entry `Energy Component Catalog`.
Data of a selected entry can be edited in view _Properties_ that is generic, too.

[[add-example-data]]Please add two or three boilers this way to have some data to play with below.

When done, you may save _First.democatalog_ so that after closing the application data will reappear if it is opened again as described above.

The generic editors don't get as far. Usually, one would like to have tables, custom property sheets, input validation, and more. Well, Sirius is all about creating nice graphical and form-based editors for data models specified in Ecore. To do this we need one more Eclipse project.


.UI Design Project

Like the *data* of our catalog is modeled as an Ecore file using a dedicated graphical editor, so will the *user interface* (tables, trees, diagrams, property views) be modeled in a Sirius `.odesign` file that lives in a special Eclipse project that we create while still in the (second) Eclipse application that hosts the data:

. Execute `File -> New -> ViewPoint Specification Project`
. Name the project `org.example.democatalog.design`, uncheck _Use default location_ as always and  create/choose a directory with the same name as the project besides to the model, edit, editor, and data project directories
. Click `Finish`.

A special editor for file `democatalog.odesign` appears automatically.
In it select `MyViewpoint` and rename it in _Properties_ to `Catalog`.
A viewpoint provides a set of representations (tables, trees, diagrams, property views) that end-users can instantiate.


.Adding a Table to the UI
 
In what follows, we work with the _democatalog.odesign_ editor.
Say, we want to add a table for boilers to the UI:

. From context menu over viewpoint _Catalogs_ execute `New Representation -> Edition Table Description` to create a new description that is automatically selected and shown in view _Properties_
. To connect the table with its data model, choose tab _Metamodels_ in _Properties_, click on _Add from registry_ and select `http://example.org/democatalog`.
. Go back to tab _General_ and enter `Boiler_table` as _Id_.
. In the green input field _Domain Class_ press key ctrl-space and choose `democatalog::EnergyComponentCatalog` from the list.

From the above _Boiler_tables_ know that they present data conforming to our `http://example.org/democatalog` data model and that boiler data are found as part -- or "below" -- the Energy Component Catalog.

Next, specify the lines to be displayed in the table:

. From context menu over _Boiler_table_ create `New Table Element -> Line`
. In tab _General_ in _Properties_, enter `Boiler_line` as _Id_:
. In the green input field _Domain Class_ press key ctrl-space and choose `democatalog::Boiler` from the list.

And now for the columns:

. From context menu over _Boiler_table_ create `New Table Element -> Feature Column`
. In tab _General_ in _Properties_, enter `Name_col` as _Id_:
. In the green input field _Feature Name_ press key ctrl-space and choose `modelName` from the list
. Repeat the above steps for `boilerType` and `installedThermalPower` accordingly.

After addition of some foreground and background styles, the design of the UI looks like this.

.Boiler Tables Design
image::BoilerTableDesign.png[BoilerTableAndProperties, role="thumb"]

Save it!

To create an instance of the table just designed double-click on `representations.aird` in the data project:

.Administration of Model and Representations
image::BoilerRepresentations.png[BoilerRepresentations, role="thumb"]

In case viewpoint `Catalogs` under header _Representations_ is still disabled as shown above, select it and press `Enable`. Then:

. Press `New...` to open a _Create Representation Wizard_
. Choose `Boiler_table` and click `Next >`
. Select `Energy Components Catalog` as data source and click `Finish`
. You are prompted for the new tables name: simply confirm the proposed name with `OK`.

[.float-group]
--
.Boiler Table with Properties View
image::BoilerTableAndProperties.png[BoilerTableAndProperties, 350, float="right", role="thumb"]

The screenshot on the right shows _new Boiler_table_ with just two entries. Details of the selected entry are editable in _Properties_.

Is your table empty? In this case you probably did not add example data using the default editor as described xref:add-example-data[above].
But you can add new Boilers any time via command `New child -> Boiler` in the context menu of `Energy Component Catalog` in section _Models_ of the representations editor depicted above.
--

Note, that you can delete boilers from the table's context menu, but currently there is no button or menu entry to create new boilers.
Such a command would have to be described in `democatalog.odesign` first.

Be aware that applications with UI design and example data launched from development environment are meant to be prototypes for the final software only.
In fact, any saved changes in the design file are instantly reflected in the UI.
During refinement of model and UI, data sets can be created, edited, and tested for usability without the need to built deployable software component. (On deployment, see parts _Accessing and Using Parameter Catalogs_ and _Build (Parameter Catalog) Applications with Eclipse Tycho_ below.)

Iteratively the UI design must be adapted to changes in data model, although some changes are automatically reflected in the generated UI, at least for default forms.
Data model changes can also can render existing XML data incompatible. There are tools for data migration, but for now, recreation of test data or manual editing of XML file is the way to go.

As you may imagine, this is just the tip of the iceberg of what can be done with the Sirius framework for designing graphical UIs.
While domain experts should be capable to create and to refine Ecore data models, the UI design of a parameter catalogs will mainly be done by software developers.
However, since the UI is not implemented by program code, but a description in an `.odesign` file, domain experts can easily enhance and tweak it, e.g. by adding or reordering columns of a table.


=== Working with Git Hosted Parameter Catalogs

Ecore data models and Sirius based UI design are used to create parameter catalog software hosted in Git repositories.
To work with these, all you need is Java, _Eclipse_ with required plug-ins for Sirius and Unit handling (see <<Setup Eclipse Modeling Tools>> for details.)


.Import Modeling Projects from Git

To connect to a Git repository open the _Import Projects from Git_ wizard via `File -> Import... -> Git -> Projects from Git -> Clone URI`. Then:

. Copy the URI of the git repository into the according input field, e.g.:
https://rs-loy-gitlab.concordia.ca/parameter-catalogs-ecore/greenery-catalog.git and provide your credentials in fields _User_ and _Password_. *Tick check box _Store in Secure Store_ and provide a master password if required!* If you don't, be prepared to be prompted for your credentials over and over again
. Click `Next >` and select a repository branch to check out, usually _main_ or _master_
. Click `Next >` and choose the directory on your file system where to store the repository, e.g.
`<user home>/git/greenery-catalog`. Here, we adhere to the convention is to have all git repositories stored in `<user home>/git/`
. After data transfer has completed, the wizard offers to _Import existing Eclipse projects_. Click `Next >` and select the project with suffix `.design`, `.model`,  `.edit` and `.editor` for import, e.g. `ca.concordia.usp.greenerycatalog.model` etc.
. Click `Finish`.

Now you can work on the data model like you did with the demo catalog. Find it under `model` in `ca.concordia.usp.greenerycatalog.model` (compare fig. <<fig-ecore-modeling-project>>).


.Catalog Data and UI Design

For data inspection and editing -- and possibly modifying the UI -- launch a new instance of the running Obeo Designer application by executing `Run -> Run Configurations...`, double-click on _Eclipse Application_ to get a _New_configuration_ and give it a meaningful name (e.g. _GreeneryCatalog_).
Then, press `Run` to start the application, close the welcome screen and open the Sirius perspective using the suited button in the top right corner of the main window.

[TIP]
====
Simply reuse the _Run Configuration_ specified above, when starting the application next time!
====

Now, import the projects that contain data and UI design, respectively:

. Execute `File -> Import...` for the import wizard
. Browse to the directory containing the projects (e.g. `<user home>/git/greenery-catalog`) and check just the project with suffix `.data` for import, e.g. `ca.concordia.usp.greenerycatalog.data`
. Click `Finish`.

When closing the application, it asks to store or dismiss any changes in data or UI design. You can also save these any time with `File -> Save All`.


.Declare Quantities

For simplicity, the demo catalog only used built-in attribute types like `EDouble`, `EInt`, or `EString`.
On the other hand, real-world parameter catalogs use a custom type named _Quantity_ that combines a numerical (double) value with a unit.

Symbols for defining units follow SI and other standards, including decimal prefixes like `m` for Milli or `G` for Giga as well as derived units, that is: `mV`, `GV` or `kW·h/m³` are all valid unit definitions.
This is all documented well in the resources mentioned in section xref:quantity-plug-ins[Add Plug-ins to deal with Quantities and Units] above, but for convenience, a table with valid units, including some specific units for urban simulation, is compiled in link:UnitsExamples.md[].

To set an attribute's type to _Quantity_ just select it in the model, choose tab _Semantic_ in view _Properties_, click on _EType_ and select _Quantity_ from the list of available types.
In the figure below, this was already done.

.Quantity Default Values
image::QuantityDefaultValues.png[QuantityDefaultValues , 400, role="thumb"]

The red arrow shows how a unit is defined in field _Default Value Literal_. E.g., attribute `densityOfDrySoil` has unit `kg/m³` assigned to it.

Note that, for this attribute, no numerical default value is given.
In contrast, `conductivityOfDrySoil` is given a unit and a default numerical value: `1.0 W/(m*K)`.

[IMPORTANT]
====
The unit of a _Quantity_ is definied by the sub-string that follows the first space character in the string given in _Default Value Literal_. The sub-string before that space is interpreted as default numerical value of the _Quantity_.
====

The rules for how a _Quantity_ default value is converted to its unit and default (initial) numerical value are very "forgiving":

* If no unit is given or it cannot be parsed to a valid unit, it will be regarded as _dimensionless_. E.g., index values, fractions and percentages are dimensionless quantities by purpose. While units may be displayed in the UI like `[kg]`, a dimensionless quantity will show up as `[]`, that is as the empty string.
* If no numerical default value is present, then the numerical value is regarded as undefined.
* You may choose to specify a quantity as dimensionless and without numeric default by leaving field _Default Value Literal_ empty (or provide some non-sensical string).

By this rules, any string -- including the empty string -- will be interpreted as a _Quantity_ somehow.


.Declare Ranges

What is the point in declaring a dimensionless quantity for an attribute, anyway, instead of just declare it `EDouble` or `EInt`? The answer is that quantities can -- and most of the time will -- have a range of valid values defined.

[.float-group]
--

.Quantity Range Definition
image::QuantityRange.png[Quantity Range , 250, float="right", role="thumb"]

As you can see in the screenshot, the allowed range of attribute values is defined by a so called Ecore annotation named `UomQuantities`.
It provides the minimal and/or maximal value for the attribute, inclusively.
If a minimal or maximal value is omitted or invalid, the range is not limited on that side.

One could add annotations to an attribute in the graphical Ecore editor under tab _Annotation_ in _Properties_, but it may be more convenient to do this in the standard editor that is opened by `Open With -> Sample Ecore Model Editor` from the context menu over the Ecore model file in _Model Explorer_.
--

In this editor, define a range like this:

. From the context menu of the attribute of interest execute `New Child -> EAnnotation` and type `http://www.hft-stuttgart.de/UomQuantities` into field `Source` as depicted above
. From the context menu of the new `UomQuantities` annotation execute `New Child -> Details Entry` and provide values for keys `min` and `max`, respectively.

[TIP]
====
The above typing is a one time effort only, since for defining further ranges, one simply copies an existing `UomQuantity` annotation from one attribute to another one and just edits the values for `min` and `max`.
====

If a catalog's end user tries to enter a number outside the given range in the UI, it will be adapted automatically to a valid value.


.Declare Tooltips for Help

Again, domain experts use a specific annotation to provide short help texts that inform end-users about an attribute's purpose, range and so on.
(These texts are displayed as tooltips when the users mouse stays on top of a question mark.)
And again, this is possible only in another kind of editor -- this time the editor that is opened on a `.genmodel` in _Model Explorer_.
Each Ecore model is accompanied by a `.genmodel` that lives besides the respective `.ecore` file. Open the required editor from its context menu with `Open With -> EMF Generator`.

The picture below shows the details. Just open the `.genmodel` tree until you can select the attribute that shall be documented.

.Quantity Documentation
image::QuantityDocumentation.png[Quantity Documentation, role="thumb"]

In its `Properties` provide the tooltip in field `Edit -> Property Description`.
In this example, the same text was also copied to `Model -> Documentation`.
These texts are automatically inserted into comments in the generated program code, so that they 
can inform a programmer that wants to use the generated API.


=== Summary

Congratulations on making it this far. What have we achieved?

We get to know _Eclipse Modeling Tools_ and created a graphical Ecore data model with one catalog class and five classes/types of domain objects therein.
Classes have been defined by name, attributes, and relationships between them, often with cardinalities.
Whenever classes shared some attributes or relationships we factored these out into super classes.
An enumeration introduced a new attribute type as a set of named values.

From this data model, we issued commands to create Java code for representing the data in memory as well as to store and retrieve them on and from disk. Methods to create, read, update and delete data objects (CRUD) were generated, too.
We implemented a prototypical user interface for this data with _Eclipse Sirius_ by providing a `.odesign` model for that very UI.

Lastly, we started working on real world parameter catalogs hosted in git repositories and introduced _Quantity_ as a custom attribute type to model quantities as numerical values with defined units.
