Published on March 15, 2014
A useful testing technique and more…
Definition Application areas Steps to create a decision table Exercise Solution to exercise 2
Decision tables are used to lay out in tabular form all possible situations which a business decision may encounter. A decision table lists causes and effects in a matrix. Each column represents a unique combination. Purpose is to structure logic 3 Cause = condition Effect = action = expected results Causes Values 1 2 3 4 5 6 7 8 Cause 1 Y, N Y Y Y Y N N N N Cause 2 Y, N Y Y N N Y Y N N Cause 3 Y, N Y N Y N Y N Y N Effects Effect 1 X X X Effect 2 X X X Combinations
Consists of three parts Condition stubs ▪ Lists condition relevant to decision Action stubs ▪ Actions that result from a given set of conditions Rules ▪ Specify which actions are to be followed for a given set of conditions 4
Business Analysis Programming Testing Hardware Design etc 5
1. List all causes in the decision table 2. Calculate the number of possible combinations 3. Fill columns with all possible combinations 4. Reduce test combinations 5. Check covered combinations 6. Add effects to the table 6
Hints: Write down the values the cause/condition can assume Cluster related causes Put the most dominating cause first Put multi valued causes last 7 Causes Values 1 2 3 4 5 6 7 8 Cause 1 Y, N Y Y Y Y N N N N Cause 2 Y, N Y Y N N Y Y N N Cause 3 Y, N Y N Y N Y N Y N Effects Effect 1 X X X Effect 2 X X X Combinations
If all causes are simplyY/N values: 2numberofcauses If 1 cause with 3 values and 3 with 2: 31 * 23 = 24 Or, use theValues column and multiply each value down the column, eg. 3*2*2*2=24 8 Number of Values to the power of the number of causes with these values
Algorithm: 1. Determine Repeating Factor (RF): divide remaining combinations by the number of possible values for that cause 2. Write RF times the first value, then RF times the next etc. until row is full 3. Next row, go to 1. 9
Find indifferent combinations – place a ‘-’ 10 Causes Values 1 2 3 4 5 6 7 8 Cause 1 Y, N Y Y Y Y N N N N Cause 2 Y, N Y Y N N Y Y N N Cause 3 Y, N Y N - - Y N Y N Effects Effect 1 X X X Effect 2 X X X Combinations Causes Values 1 2 3 4 5 6 7 Cause 1 Y, N Y Y Y N N N N Cause 2 Y, N Y Y N Y Y N N Cause 3 Y, N Y N - Y N Y N Effects Effect 1 X X Effect 2 X X X Combinations Join columns where columns are identical Tip: ensure the effects are the same
Checksum For each column calculate the combinations it represents A ‘-’ represents as many combinations as the cause has Multiply for each ‘-’ down the column Add up total and compare with step 2 11 Causes Values 1 2 3 4 Cause 1 Y, N Y Y Y N Cause 2 Y, N Y N N - Cause 3 Y, N - Y N - Effects Effect 1 X X Effect 2 Checksum 2 1 1 4 8 Combinations
Read column by column and determine the effects One effect can occur in multiple test combinations 12 Causes Values 1 2 3 4 Cause 1 Y, N Y Y Y N Cause 2 Y, N Y N N - Cause 3 Y, N - Y N - Effects Effect 1 X X Effect 2 X X Checksum 2 1 1 4 8 Combinations
A marketing company wishes to construct a decision table to decide how to treat clients according to three characteristics: Gender, City Dweller, and age group: A (under 30), B (between 30 and 60), C (over 60).The company has four products (W, X,Y and Z) to test market. ProductW will appeal to female city dwellers. Product X will appeal to young females. ProductY will appeal to Male middle aged shoppers who do not live in cities. Product Z will appeal to all but older females. 13
--Identify Conditions &Values The three data attributes tested by the conditions in this problem are 1. gender, with values M and F; 2. city dweller, with valueY and N; and 3. age group, with values A, B, and C as stated in the problem. 14
2. Compute Maximum Number of RulesThe maximum number of rules is 2 x 2 x 3 = 12 3. Identify Possible ActionsThe four actions are: market productW, market product X, market productY, market product Z. 4. Enter All Possible RulesThe top of the table would look as follows: Note that all combinations of values are present. 15
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