The document discusses decision tables as a programming tool. It provides a brief history of decision table usage, describes common decision table structures and formats, and discusses techniques for simplifying, optimizing and generating code from decision tables. Examples are given of decision table usage for tasks like order processing and discount calculation. The speaker's background and the capabilities of RapidGen's decision table language are also summarized.

1. rapidgen.com
Decision Tables as a
Programming tool
Howard Rogers
Director Technical Support
howard.rogers@rapidgen.com

2. Agenda
• A brief history
• Decision table structures
• Rule formats
• Rule redundancy, reduction and optimisation
• Relevance testing
• Some practical examples
• Current examples of use
• Future developments
• Questions and Answers
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3. Speaker
• Statistics & Operation Research
• UK National Health Service
• 35 years IT
• Decision table based languages and compilers
• Query & reporting tools
• Generic file & database access
• Brief interlude with RTPI
• Technical support
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4. History
• NASA
• Morgan Crucible – LITA – List &Tabulate
• TABN for ICL 1900 series mainframes
• (DE)TAB-360 for IBM System/360
• UNITAB for UNIVAC
• HTAB for Honeywell
• TAB-11 for RSTS/E on PDP-11
• FTL6/DTPL for ICT 1900 series
• RPL-11 for RT-11, RSTS/E, RSX-11 on PDP-11
• RPL-3 for IBM System/3
• Filetab-D for x86 and PDP-11, OpenVMS VAX
• FPL - IBM PCs and compatibles.
• RPL, Rapid-Expert and expertGenius extended syntax for Microsoft
Windows, Unix, Linux and OpenVMS,VAX, Alpha & Itanium
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5. History
• Excel – query tables
• COPE – Translate DTs to COBOL
• LogicGEM – Translate to BASIC,C, C++, FORTRAN, Pascal etc etc
• CCIDE – Pre-processor for BASIC, JAVA, CC, C++, BASH, QB, VB,
and EX(euphoria)
• Silk (Simple In-line Logic Kompiler) converting decision tables to
Cobol code and vice versa.
• PASPREP – Pascal preprocessor
• Many many others
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6. Decision table structure
• Conditions
• Actions
• Condition rules
• Action rules
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7. Single Condition Decision Table
Condition Stubs Rules
Action Stubs Actions
Quantity > 100 Y N
Apply 20% Discount X -
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8. Quantity > 100 Apply 20% Discount
Y
N
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Decision Tables
Horizontal vs Vertical
Condition Stubs Action Stubs
Rules Actions
8
X
-

9. Multiple Single Decision Table
Condition Stubs Rules
Action Stubs Actions
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Quantity > 100 Y Y N N
Cash payment Y N Y N
Apply 20% Discount X - - -
Apply 10% Discount - X - -
Apply 5% Discount - - X -
No discount - - - -
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10. Multiple Condition DTs
• Complete True/False Y N require
2^Conditions rules
• 3 Conditions – 8 rules
• 4 Conditions – 16 rules
• etc
• Use of “-” to reduce completeness
• Practical limit 32
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11. Five Conditions – One rule
Initially no discount
Quantity > 100 Y -
Cash payment Y -
Credit_check Y -
Product type is laptop Y -
Employee N -
Apply 5% Discount X -
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12. Multiple Section Decision Table
Quantity > 100 Y Y N N
Cash payment Y N Y N
Apply 20% Discount X - - -
Apply 10% Discount - X - -
Apply 5% Discount - - X -
No discount - - - -
Discount_amount < $1 Y -
No discount X -
Discount amount > $1000 Y -
Set discount $1000 X -
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13. Simplifying Decision Tables 1
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1 2 3 4 5 6 7 8
13
Credit limit
exceeded
Y Y Y Y N N N N
Cash payment Y Y N N Y Y N N
Special clearance Y N Y N Y N Y N
Accept order X X X - X X X X
Reject Order - - - X - - - -

14. Simplifying Decision Tables 2
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1&2 3 4 5 6 7 8
14
Credit limit
exceeded
Y Y Y N N N N
Cash payment Y N N Y Y N N
Special clearance - Y N Y N Y N
Accept order X X - X X X X
Reject Order - - X - - - -

15. Simplifying Decision Tables 3
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1&2 3 4 5&6 7&8
15
Credit limit
exceeded
Y Y Y N N
Cash payment Y N N Y N
Special clearance - Y N - -
Accept order X X - X X
Reject Order - - X - -

16. Simplifying Decision Tables 4
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1&2 3 4 567&8
16
Credit limit
exceeded
Y Y Y N
Cash payment Y N N -
Special clearance - Y N -
Accept order X X - X
Reject Order - - X -

17. Simplifying Decision Tables 5
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4 123567&8
Credit limit
exceeded
Y ELSE
Cash payment N -
Special clearance N -
Accept order - X
Reject Order X -

18. Optimising Decision Tables
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1 2 3 4 5 6 7 8
18
Credit limit
exceeded
Y Y Y Y N N N N
Cash payment Y Y N N Y Y N N
Special clearance Y N Y N Y N Y N
Accept order X - X - X X X X
Reject Order - X - X - - - -
2&4 123567&8
Credit limit
exceeded
Y ELSE
Special clearance N -
Accept order - X
Reject Order X -

19. ELSE Rule
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4 123567&8
Credit limit
exceeded
Y ELSE
Cash payment N -
Special clearance N -
Accept order - X
Reject Order X -

20. Simplifying Decision Tables –
Extended entry
TRANSKEY GT MASTKEY Y - - - ELSE
TRANSKEY EQ MASTKEY - Y Y - -
TRANSKEY LT MASTKEY - - - Y -
TRANSTYPE = “I” - - - Y -
TRANSTYPE = “D” - - Y - -
TRANSTYPE = “A” - Y - - -
CALL PROCESS_MATCH - X - - -
CALL PROCESS_MISS - - X - -
CALL PROCESS_ADD - - - X -
CALL NEXT_TRANS - X X X -
CALL NEXT_MAST X X X - -
REPEAT X X X X -
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21. Simplifying Decision Tables –
Extended entry
TRANSKEY ? MASTKEY > = = < ELSE
TRANSTYPE = “?” - A D I -
CALL PROCESS_? - MATCH MISS ADD -
CALL NEXT_TRANS - X X X -
CALL NEXT_MAST X X X - -
REPEAT X X X X -
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22. Ambiguity or Multi-ruling?
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Set discount
Initialise DISCOUNT_PERC
Cash payment Y - - -
Special offer - Y - -
Good credit history - - Y -
DISCOUNT_PERC + ? 5 10 2 -

23. |--------------------------------------------------|
|--------------------------------------------------|
|# |STATEMENT 1 2 3 4 5 6 7 8 |
|--------------------------------------------------|
|C1 |Cash payment |y |y |y |y |n |n |n |n |
|C2 |Special offer |y |y |n |n |y |y |n |n |
|C3 |Good credit history |y |n |y |n |y |n |y |n |
|==================================================|
|A1 |Discount initialise | | | | | | | | |
|A2 |Discount + 5 |X |X |X |X | | | | |
|A3 |Discount + 10 |X |X | | |X |X | | |
|A4 |Discount + 2 |X | |X | |X | |X | |
|--------------------------------------------------|
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Code generation 1
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24. Generation – Nested If/else 1
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{
if ((Cash payment)) {
if ((Special offer)) {
if ((Good credit history)) {
/* rule 1 */
Discount + 5;
Discount + 10;
Discount + 2; }
else {
/* rule 2 */
Discount + 5;
Discount + 10; }
}
else {
if ((Good credit history)) {
/* rule 3 */
Discount + 5;
Discount + 2; }
else {
/* rule 4 */
Discount + 5;
}
}
}
else {

25. Generation – Nested If/else 2
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if ((Special offer)) {
if ((Good credit history)) {
/* rule 5 */
Discount + 10;
Discount + 2;
}
else {
/* rule 6 */
Discount + 10;
}
}
else {
if ((Good credit history)) {
/* rule 7 */
Discount + 2;
}
else {
/* rule 8 */
}
}
}
}

26. Generation – Case Switch 1
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{
if ((Cash payment)) {
if ((Special offer)) {
if ((Good credit history)) {
rule_number = 1;
}
else {
rule_number = 2;
}
}
else {
if ((Good credit history)) {
rule_number = 3;
}
else {
rule_number = 4;
}
}
}

27. Generation – Case Switch 2
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else {
if ((Special offer)) {
if ((Good credit history)) {
rule_number = 5;
}
else {
rule_number = 6;
}
}
else {
if ((Good credit history)) {
rule_number = 7;
}
else {
rule_number = 8;
}
}
}

28. Generation – Case Switch 3
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switch (rule_number) {
case 1:
Discount + 5;
Discount + 10 ;
Discount + 2;
break;
case 2:
Discount + 5;
Discount + 10;
break;
case 3:
Discount + 5;
Discount + 2;
break;
case 4:
Discount + 5;
break;

29. Generation – Case Switch 4
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case 5:
Discount + 10;
Discount + 2;
break;
case 6:
Discount + 10;
break;
case 7:
Discount + 2;
break;
case 8:
break; }

30. rapidgen.com
Generation – Rule List 1
30
{
if ( ((Cash payment)) &&
((Special offer)) &&
((Good credit history)) ) {
Discount + 5; Discount + 10; Discount + 2;
}
if ( ((Cash payment)) &&
((Special offer)) &&
(!(Good credit history)) ) {
Discount + 5; Discount + 10;
}
if ( ((Cash payment)) &&
(!(Special offer)) &&
((Good credit history)) ) {
Discount + 5; Discount + 2;
}
if ( ((Cash payment)) &&
(!(Special offer)) &&
(!(Good credit history)) ) {
Discount + 5;
}

31. rapidgen.com
Generation – Rule List 2
31
if ( (!(Cash payment)) &&
((Special offer)) &&
((Good credit history)) ) {
Discount + 10; Discount + 2;
}
if ( (!(Cash payment)) &&
((Special offer)) &&
(!(Good credit history)) ) {
Discount + 10;
}
if ( (!(Cash payment)) &&
(!(Special offer)) &&
((Good credit history)) ) {
Discount + 2;
}
if ( (!(Cash payment)) &&
(!(Special offer)) &&
(!(Good credit history)) ) {
}
}

32. rapidgen.com
Generation – Rule Mask
32
{Mask = 11111111
{if ( Cash payment)
Mask AND 11110000;
}
{if ( Special Offer)
Mask AND 11001100;
}
{if (Good credit history)
Mask AND 10101010;
}
{if (Mask AND 11110000)
Discount + 5 ;
}
if (Mask AND 11001100)
Discount + 10;
}
if (Mask AND 10101010)
Discount + 2;
}

33. • Succinct code
• Reduces repetition of condition testing
• Reduced repetition of action code
• Fast execution
• No frequency/cost weighting of rules
needed
•  All conditions are evaluated
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Rule masking
33

34. AGE > 50 Y - -
CALL ADJUST_COVER Y - -
TRANSKEY LT MASTKEY - Y -
LOOKUP MASTER TRANSKEY - Y -
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Relevance Testing
Some operations require dynamic masking where actions
may be performed or I/O occurs
34

35. AGE > 50 Y - -
COVER + 20 R - -
TRANSKEY LT MASTKEY - Y -
DISPLAY “Message” - R -
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Relevance Testing
Dynamic masking again needed when Actions are inserted
into condition section of Decision Table using “R”
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36. CALL Credit_limit_exceeded Y ELSE
CALL Cash_payment N -
CALL Special_clearance N -
CALL ACCEPT_ORDER - X
CALL REJECT_ORDER X -
CALL Credit_limit_exceeded Y ELSE
CALL Cash_payment N -
CALL Special_clearance N -
GOTO ACCEPT_ORDER - X
CALL_I Variable_name X -
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Decision table linkage
CALLs to other DTs or object library routines
GOTO link to DT or indirect CALL
36

37. Requirements of a DT language
• Feature rich language
• Support for multiple data types
• Unmatched data type comparison
• Good string handling/text manipulation
• Access external routines/library functions
• File, database, object and data dictionary
• Callable access from other products
• Source code maintenance, version control
• Compiled and portable execution
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38. Decision Tables in other products
• Uses GUI in SAP HANA Studio
• SAP Parameter/Database DTs
• Alternate use via Excel spreadsheets
• SMARTS
• OpenRules Engine
• Decision First Modeler
• Drools
• Many more …
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39. Usage of RPL - expertGenius
• Self compiling
• Cross compiling
• Source of Genius Suite
• Code writing and compiling 4GL and RAD
toolset
• Complete layered application suites
• Reporting – fixed logic
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40. Genius deployment
• Aerospace factory tracking systems
• Mobile phone billing systems
• Payroll data mining
• HR system ad-hoc querying
• Newspaper distribution system
• Stock control
• Sales order dashboard & EIS
• Web based on-line parts ordering
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41. CDT Callable Decision Tables
• Simple calculator
• Calculator code
• Tax formula (UK)
• Tax calculator
• Tax code
• CDT Callable access from other
languages and applications
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42. Future developments
• Extend range of generic database access
• Ports to new architectures
• Macro expansions for FEEL or S-FEEL
• GUI extensions
• CDT Callable access from other
languages and applications
• Cloud based compiler
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43. rapidgen.com
Decision Tables as a
Programming tool
Howard Rogers
Director Technical Support
howard.rogers@rapidgen.com
howard.rogers@rapidgen.co.uk