The support of Decision Modeling features and concepts in tooling

Jan Vanthienen Jan.Vanthienen@kuleuven.be

Thibaut Bender

Faruk Hasić

Department of Decision Sciences

and Information Management

Leuven Institute for Research on

Information Systems (LIRIS)

17/09/2018 1

Presented by

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Jan VanthienenKU LeuvenFaculty of Economics and Business Business Information Systems Group

Research and teaching:• Business rules, processes and information systems• Decision models & tables• Business intelligence & Analytics• Information & Knowledge Management

• IBM Faculty Award

• Belgian Francqui Chair 2009 at FUNDP

- Bpost bank Research Chair

- Colruyt-Symeta Research Chair Smart Data and Decisions

- IBM Fund Intelligent Business Decision Making

- Microsoft Research Chair on Intelligent Environments

- PricewaterhouseCoopers Chair on E-Business

Email: jan.vanthienen@kuleuven.be

Outline

1. Research context, problem statement, analysis methodology

2. Tools and tests

3. Results

4. Limitations and conclusions

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Research context

• Decision Modeling and Notation (DMN)

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Problem Statement

• To which extent are important Decision Model and Notation (DMN) features and concepts supported by tooling?

• Not a tool comparison

• Not an alternative for the automated DMN Technology Compatibility Kit TCK (https://github.com/agilepro/dmn-tck)

• Goal• Which DMN elements (decision requirements diagrams, decision

logic specifications, the expression language) are commonly present in current decision modeling/execution tools.

• Which modeling features are considered important by tool vendors.

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Analysis methodology

• 13 tool vendors responded positively to participate in the research and provided access (and documentation) to their tool. We promised anonymity of test results.

• We built/executed a number of decision models in each of the tools.

• We manually modeled in the 13 tools:• Decision Requirements Diagram = graphical model

• Decision Tables

• Friendly Enough Expression Language (FEEL) = data types and functions

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13 out of 19 tools (Decision Management Community)

• Actico• AlfrescoActivity• Avola• BizzDesign• Blueriq• Camunda• DecisonsFirstModeler• Drools• Fico• Flexrule• IBM• IDIOM• Onedecision• OpenRules• RapidGen• Sapiens• Signavio• Sparkling logic Pencil modeller• TrisoTech

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Decision requirements (10/13 tools)

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Figure 1: Decision Requirement Diagram support per element

,000%

20,000%

40,000%

60,000%

80,000%

100,000%

75,000%

DRD elements

Decision object Input object

Knwoledge source Business knowledge object

Information Requirement Knwoledge Requirement

Authority Requirement (Text Annotation) + Association

• Results based on tools supporting DRD

• Link between object & requirement is 100%

• Support relatively good (AVG 75%)

Tools are elements of this category when they comply with at least one

feature of the standard developed for modeling decisions.

Decision tables

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Figure 2: Decision Table elements: % support over all DMN tools

0%10%20%30%40%50%60%70%80%90%

Unique Any First Priority Output

Order

Rule

order

Collect

single hit Multiple hit

Decision Table elements • Decision table hit policies

• No general (uniform) 100% supported policy

Decision table features

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Decisio

n Logic

Decision

Table

Unique 83,33% 79,17%

Any 83,33%

First 75,00%

Priority 75,00%

Output Order 75,00% 73,81%

Rule order 83,33%

Collect list 58,33%

+ 75,00%

< (min) 75,00%

> (max) 75,00%

# (count) 75,00%

Average 50,00%

rules as rows 100,00%

rules as colums 0,00%

crosstab 0,00%

Multiple

output83,33%

Standard Hit policy table notation 41,67%

Multiple

hit

single hit

S-Feel

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Figure 3: S-Feel % Adoption

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Average Emptysymbol (-)

number string boolean days &time

duration months &years

date

S-Feel

FEEL syntax

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Figure 4: FEEL elements and their % support by DMN applications

0%10%20%30%40%50%60%70%80%90%

100%

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FEEL syntax

FEEL functions

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Figure 5: FEEL functions average support for each function category

0%

20%

40%

60%

80%

100%

Boolean

Functions

String

Functions

List Functions

Numeric

Functions

FEEL functions

not(negand)

substring(string, startposition, length?)

string length(string)

upper case(string)

lower case(string)

substring before (string, match)

substring after (string, match)

replace(input, pattern,replacement, flags?)

contains(string, match)

starts with(string, match)

ends with(string, match)

matches(input, pattern, flags?)

list contains(list, element)

count(list)

min(list)

max(list)

sum(list)

mean(list)

and(list)

or(list)

sublist(list, start position,length?)

append(list, item…)

concatenate(list…)

insert before(list,position, newItem)

remove(list, position)

reverse(list)

index of(list, match)

union(list…)

distinct values(list)

flatten(list)

decimal(n, scale)

floor(n)

ceiling(n)

String functions List functions Numeric functions

Clustering

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Figure 6: Clustering k=5 implementation Cluster 2(modelling) & 3 (decision table ) elements

0%

20%

40%

60%

80%

100%

Clustering: modeling and decision table elements

Cluster 2 Cluster 3

cluster 0: most FEEL functions

are covered.

cluster 1: covers extra

functionalities that vendors

implemented and text

annotations.

cluster 2: is mostly focused on

the modeling functions of DMN

cluster 3: decision table

functionalities like most hit

policies are also covered in this

cluster.

cluster 4: The last cluster

implements data elements

specified in the S-FEEL and

FEEL standard for basic

calculations or representations of

intervals.

Overall results

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Tool A Tool B Tool C Tool D Tool E Tool F Tool G Tool H Tool I Tool J Tool K Tool L Tool M Average

total 83,4% 84,0% 30,4% 91,0% 47,7% 48,9% 40,3% 92,3% 70,5% 31,0% 46,1% 77,0% 44,4% 60,5%

DRD 100,0% 93,2% 22,7% 100,0% 47,7% 0,0% 0,0% 100,0% 93,2% 70,5% 70,5% 93,2% 0,0% 60,8%

Decision Table 96,8% 77,8% 36,5% 96,8% 42,9% 96,8% 93,7% 96,8% 93,7% 0,0% 11,1% 81,0% 96,8% 70,8%

S-FEEL 72,8% 87,7% 72,8% 100,0% 74,1% 87,7% 87,7% 87,7% 0,0% 0,0% 74,1% 100,0% 87,7% 71,7%

FEEL 18,1% 69,5% 18,1% 51,2% 43,8% 68,9% 22,8% 65,5% 0,0% 0,0% 34,1% 14,4% 41,5% 34,4%

XML 100% 100% 0% 100% 0% 100% 0% 100% 0% 0% 0% 0% 100% 46,2%

Limitations

• Only 13 tools

• Manual testing

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Summary

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0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

total

DRD

Decision Table

S-FEEL

FEEL

XML

DMN category support

Tool A Tool B Tool C Tool D Tool ETool F Tool G Tool H Tool I Tool JTool K Tool L Tool M Average

Figure 9: support by tool against DMN categories

Conclusions

• FEEL support is low

• Still a gap between Requirements modeling tools and Decision table execution tools

• No hit policy has a 100% support

• Vertical and crosstab formats are not supported

• Hit policy is only indicated in 42% of the tools

• 5 tools do well

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Final verdict

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0

7

1

5

[0-25%[ [25-50%[ [50-75%[ [75-100%[

Distribution Tool scoring

Thank you

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