Welcome to the cDMN documentation!

1. What is cDMN?

Constraint Decision Modeling and Notation (or cDMN for short) is an extension to the DMN standard, which is managed by the Object Management Group (OMG). An explanatory summary of DMN is listed below.

From the DMN website:

DMN is a modeling language and notation for the precise specification of business decisions and business rules. DMN is easily readable by the different types of people involved in decision management. These include: business people who specify the rules and monitor their application; business analysts.

DMN models are created by chaining together decisions. Every decision is defined by a decision table. For example, the table below shows how to decide the dish to cook based on the season and the amount of guests. Every decision table has input variables, and an output variable. Each row of a table denotes a possible combination of input variables, which define one or more outputs. This way, decisions can be represented in a readable manner. If for example Season is Winter and there are 10 guests, row 2 dictates that the Dish is Pasta.

Decide what to eat
U Season NumberOfGuests Dish
1 Winter ≤ 8 Spareribs
2 Winter > 8 Pasta
3 Summer > 10 Light Salad
4 Summer ≤ 10 Beans Salad
5 Spring < 10 Stew
6 Spring ≥ 10 Steak

cDMN extends standard DMN by adding constraint reasoning, variable quantification, more expressive data representations, and more. Because of these additions, cDMN has a couple advantages over DMN.

  • Constraints increase expressivity and flexibility.

  • Models scale better with input size.

  • Models are more compact and straightforward.

  • Modelling complex systems becomes possible.

cDMN is part of ongoing research by Simon Vandevelde and Joost Vennekens at the EAVISE group, KU Leuven University. If you are interested in learning more about how cDMN could help you and/or your company, contact us.

For those who want to read more about the theoretical side of cDMN, you can read our paper titled “Tackling the DM Challenges with cDMN: a Tight Integration of DMN and constraint reasoning”.

cDMN has also been presented at two conferences: the more theoretical RuleML+RR2020 presentation can be viewed here, and the more practical DecisionCAMP20 presentation can be viewed on their youtube.

2. How do I use it?


The cDMN Notation page details all cDMN features and how to use them. If you are interested in learning cDMN, it is recommended to read/skim through this page, and then view the concrete cDMN examples to see cDMN in action.

Using the notation is straightforward: models can be created in any spreadsheet editing software you like. If you wish to execute your models, you can use our cDMN Solver. Although, keep in mind that our solver currently only supports cDMN models in the .xlsx format.



We are working on a tool that lets you interact with cDMN directly, without installation. A preview version is available for free.

The cDMN solver consists of a converter written in Python 3, and an off-the-shelf knowledge reasoning engine (IDP-Z3 system). Information on the installation of the cDMN solver can be found here: cDMN Solver. The solver fully works on Windows, Mac and Linux. Furthermore, we are also planning on creating a browser-based tool, which everyone could run, regardless of OS.


More information on the usage of the cDMN solver can be found at 2. Usage.


For examples, see the Examples page.

3. Can I also use it as a tool for standard DMN?

Yes you can! The cDMN solver supports everything in the normal DMN standard, besides boxed expressions and tables with the C hit policy. All other hit policies (U, A, F, C#, …) are supported. The DMN specification can be either be in the form of a spreadsheet, or in the XML format as specified in the standard. An explanation on how to use cDMN for DMN is given at the 2. Usage page.

On top of our cDMN tool, we also bundle a Python DMN API, which serves as an embeddable reasoning engine. This API allows for querying the DMN specification for information (such as input names, output names, …), and allows for setting variable values and propagating them throughout the model.. A guide on the usage of the API can be found at Python DMN API.

We also have a tool which integrates a DMN editor with an IDP-based user-friendly interface, called DMN-IDP. You can try it out for yourself at the online DMN-IDP demo.

4. How to contribute

cDMN’s source code is hosted on this GitLab repo under the GNU GPLv3 license. There’s also documentation available for developers, over at The cDMN developer reference.

5. How to reference

If you used cDMN in a publication or in other works, please reference us as follows:


  title = {Tackling the {{DM}} Challenges with {{cDMN}}: {{A}} Tight Integration of {{DMN}} and Constraint Reasoning},
  year = {2021},
  journal = {Theory and Practice of Logic Programming},
  pages = {1--24},
  publisher = {{Cambridge University Press}},
  doi = {10.1017/S1471068421000491}

Direct cite:

VANDEVELDE, S., AERTS, B., & VENNEKENS, J. (2021). Tackling the DM Challenges with cDMN: A Tight Integration of DMN and Constraint Reasoning. Theory and Practice of Logic Programming, 1-24. doi:10.1017/S1471068421000491

Full Documentation Contents: