
## Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees
Ruiwei Wang, Roland H.C. Yap
Keywords: Constraint Satisfaction And Optimization (CSO)
AAAI/2022/Proceedings/20300 - Encoding Multi-Valued Decision Diagram Constraints as Binary Constraint Trees.pdf

### Implementation
_Given the documentation given by the authors on the method, how much time investment would it be to re-implement the method from scratch?_

[7]

The authors provide sources for algorithms used but not for their own code. The other implementation sources will help, and many pieces of pseudo code are given. The problems used also have sources.

### Data
_Given the data description in the documentation, how much effort take to either: Find the same dataset the authors used, or similar datasets and defend the comparability, or acquire one from scratch?_

[1]

(4/4)

The authors use various benchmark problems, provide details on them and direct links to their source. 

### Configuration 
_Given the (hyper)parameters, including semantic parameters, of the method: How much effort would it take to acquire the algorithm configurations used for their results, and compare against their budgetary constraints?_

[1]

Their method is seemingly parameter free, and details for the other used algorithms are provided. 

### Experimental Procedure
_Given the experimental set-up of the work, how difficult is it to set up a new experiment, similar to those presented in the original work, with the same procedure?_

[2]

The authors state their metrics in table 1, but do not give a description. The application of the methods on the data is straightforward. 

### Expertise
_How much effort would it take to acquire the expertise required to reproduce the work independently relying on the available documentation?_

[6]

The method requires a deep understanding of constraint satisfaction, logic, graphs/(binary) trees representations.
