Extracting Business

Rules and Removing

Duplication With IRIS

Wei Wu, École Ploytechnique de Montéal

Stéphane Vaucher, Benchmark Consulting

Outline

Business Rule (BR)

Problem

Previous Works

BR Extraction

Detect Duplication

Examples

TODO

Business Rule

Business rules (BRs) are statements that prevent,

cause, or suggest business activities to happen.

- The GUIDE Business Rules Project

Example:

If the driver age under 25, car rent rate is $80 per

day, otherwise, it is $60 per day.

Business Rule

OMG Semantics of Business Vocabulary and

Business Rules (SBVR)

Conceptual Model

Business Rule

Rule: If the driver age under 25, car rent rate is $80 per day, otherwise, it is $60 per day.

Term:

Driver age

Car rent rate

Fact:

The driver age under 25

Set car rent rate to $80

Set car rent rate to $60

Problem

Written by business analysts

Implemented in business systems

Documents and implementations are not well

synchronized

Actual BRs are only in the source code

No reliable way to extract them

Previous Works

Erik Putrycz and Anatol W. Kark, Recovering Business Rules from Legacy Source Code, the Proceedings of The International RuleML Symposium on Rule Interchange and Applications (RuleML-2007), 2007

Harry M. Sneed, Extracting Business Logic from existing COBOL programs as a basis for Redevelopment, Proceedings of the 9th International Workshop on Program Comprehension (IWPC’01), 2001

Huang et al., Business Rule Extraction from Legacy Code, COMPSAC '96 Proceedings of the 20th Conference on Computer Software and Applications, 1996

Harry M. Sneed and Katalin Erdos, Extracting Business Rules from Source Code, WPC '96 Proceedings of the 4th International Workshop on Program Comprehension, 1996

Softwareminingʹs BRE Toolkit, http://www.softwaremining.com/services/Business_Rule_Extraction.jsp

Limitations

Not KDM based - Language specific

Not distinguish business and non-business

variable.

Need manually-identified variable-of-interest

Not handle duplication

Term Unit Extraction

DB Related DataElements

ColumnSet – ItemUnit

ColumnSet – InDataRelations – DataModel –

DataElements

DataModel – DataAction - DataElement

DB Related DataElements - TermUnit

Identify DB-related Actions

ActionElements InReads and InWrites of DB Related DataElements

Top-level Conditions if(no-db-realted-Data){

if(db-related-data1){

if(db-related-data2){

}

}

if(db-related-data3){

}

}

Identify Top-level Condition

Condition not dominated by any condition which

accesses DB-realted DataElement

To detect not-top-level conditions

Get basic-block (BB) of each condition

Get all the dominators of the BB

Get the InFlow of the first ActionElement of each dominator

If the InFlow is TrueFlow or FalseFlow and the condition of

the Flows accesses some DB related DataElement

RuleUnit Extraction 2-1

Create RuleUnit for the TrueFlow (FlaseFlow)

of each top-level condition

Put the condition to the implementation list of

the RuleUnit

Create a FactUnit for the condition

Create a ConceptualRole for the FactUnit and

put it to the ConceptualElement list of the Rule

Unit

RuleUnit Extraction 2-2

Create a FactUnit for each ActionElement in the

branch

Create a ConceptualRole for the FactUnit and put it to

the ConceptualElement list of the Rule Unit

Create a normalized ID for the RuleUnit based on all

its ConceptualRoles

If there’s another RuleUnit with the same ID, just add

the implementation list to that RuleUnit.

Otherwise, add the RuleUnit to the Conceptual Model

ActionElement Normalization

Intermediate Presentation

Left - OutReads

Operator - Type

Right – OutReads

Conditions

NNF

DNF

ActionElement Normalization

Alphabetical Normalization

b == a -> a == b

b < a -> a > b

d>c && b<a -> a>b && c<d

Examples

BR:

121810 EVALUATE SQLSTATE 02443500

121810 WHEN SQL-OK 02443600

121810 IF WORK-HV-TXL-CLS-WASH-SALE-AMT >= 0 02443700

121810 IF WORK-HV-TXL-CLS-RECORD-DEL-SW = 'N' AND 02443800

121810 TAXL-TRANS-TYPE-NO = 930 02443900

012211 PERFORM RECALCULATE-AVG-WASH-QTY 02444000

121810 SET PROCESS-AVG-WASH 02444100

121810 TO TRUE 02444200

121810 ELSE 02444300

121810 IF WORK-HV-TXL-CLS-RECORD-DEL-SW = 'Y' AND 02444400

121810 (TAXL-TRANS-TYPE-NO = 500 OR 600) 02444500

012211 PERFORM RECALCULATE-AVG-WASH-QTY 02444600

121810 SET PROCESS-AVG-WASH 02444700

121810 TO TRUE 02444800

121810 END-IF 02444900

121810 END-IF 02445000

121810 END-IF 02445100

121810 WHEN OTHER 02445200

121810 PERFORM ERROR-AVG-WASH 02445300

121810 END-EVALUATE.

Examples

Duplicated

080306 IF HV-TXL-MST-OPEN-DATE IS LESS THAN 00862200

091906 WORK-TAXL-UPDT-DIV-EX-DT-DB2 OR 00862300

091906 HV-TXL-MST-OPEN-DATE IS EQUAL TO DF-NINES-DATE 00862400

080306 PERFORM UPDATE-LIQUIDATION-PAYMENT 00862500

080306 END-IF 00862600

IF TAXL-QTY IS NOT EQUAL TO ZERO 00862700

PERFORM FETCH-ROW-TXL-OPEN-FIFO 00862800

END-IF

080306 IF HV-TXL-MST-OPEN-DATE IS LESS THAN 00869400

091906 WORK-TAXL-UPDT-DIV-EX-DT-DB2 OR 00869500

091906 HV-TXL-MST-OPEN-DATE IS EQUAL TO DF-NINES-DATE 00869600

080306 PERFORM UPDATE-LIQUIDATION-PAYMENT 00869700

080306 END-IF 00869800

IF TAXL-QTY IS NOT EQUAL TO ZERO 00869900

PERFORM FETCH-ROW-TXL-OPEN-FIFO 00870000

END-IF

Examples

Data ActionElements: 2,084

Code ActionElements: 47,699

IF conditions: 2,724

DB related ActionElements: 12,195

DB related IF conditions is 621

Top-level if conditions is 591

ActionElements in BRs are 2,038

Ongoing Works

Compute the percentage of the ActionElements

involved in BRs

Compare with using graph matching techniques

to identify duplicated or similar BRs

Future Works

Get feedback from business people

Multi-objective way to detect duplicated or

similar BRs

Peephole Optimization

Remove irrelevant ActionElements

(Usedef/Defuse)

Inter-procedural analysis

Thank You!

Extracting Business

Rules and Removing

Duplications With IRIS