Chapter 8 Structuring System Requirements: Logic Modeling 9.1

Learning Objectives Use Structured English as a tool for representing steps in logical processes in data flow diagrams Use decision tables and decision trees to represent the logic of choice in conditional statements Select among Structured English, decision tables, and decision trees for representing processing logic 9.2

Logic Modeling Data flow diagrams are good for identifying processes but do not show the logic inside the processes Logic modeling involves representing internal structure and functionality of processes depicted on a DFD. These processes appear on DFDs as little more than black boxes. Logic modeling within a process means how data is transformed into information. Logic modeling can also be used to show when processes on a DFD occur Logic modeling will not reflect the structure or syntax of a particular programming language. 9.3

Logic Modeling Deliverables and Outcomes Structured English representation of process logic Decision Table representation Decision Tree representation 9.4

Modeling Logic with Structured English Modified form of English is used to specify the logic of information processes Uses a subset of English Action verbs (read, write, print , sort, move, merge etc Noun phrases No adjectives or adverbs No specific standards; each analyst will have his or her own particular dialect of structured English 9.5

Modeling Logic with Structured English Structured English is used to represent all three processes typical to structured programming: Sequence, conditional statements and repetition. Sequence statements require no special structure but can be represented with one sequential statement following another. 9.6

Modeling Logic with Structured English Sequence Statements can be represented Statement 1; Statement 2; Statement 3;

Modeling Logic with Structured English Conditional statements can be represented as If conditions statements Syntax BEGIN IF IF condition 1 THEN statement 1 ELSE DO statement 2 ENDIF

Modeling Logic with Structured English BEGIN IF IF quantity-in-stock is less than Minimum-order-quantity THEN GENERATE new order ELSE DO nothing ENDIF

Modeling Logic with Structured English Case statements READ variable SELECT CASE CASE 1 condition1 statement 1 CASE 2 condition 2 statement 2 CASE 3 condition 3 statement 3 …………… CASE4 condition n statement n END CASE

Modeling Logic with Structured English Case statements READ Quantity-in-stock SELECT CASE CASE 1 (Quantity-in-stock greater than Minimum-order-quantity) DO nothing CASE 2 (Quantity-in-stock equals Minimum-order-quantity) CASE 3 (Quantity-in-stock less than Minimum-order-quantity) GENERATE new order CASE4 (Quantity-in-stock is zero i.e. out of stock) INITIATE emergency reorder routine END CASE

Modeling Logic with Structured English Repetition can take the form of DO-UNTIL loops or DO - WHILE loops. A DO-UNTIL loop might be represented as follows: DO READ variable(s) BEGIN IF IF condition1 THEN statement 1 ELSE statement 2 END IF UNTIL End-of-file

Modeling Logic with Structured English A WHILE- DO loop might be represented as follows: READ variable(s) WHILE NOT End-of-file DO BEGIN IF IF condition1 THEN statement 1 ELSE statement 2 END IF END DO

Modeling Logic with Structured English DO READ Inventory Records BEGIN IF IF Quantity-in-stock less than Minimum-order- quantity THEN GENERATE new order ELSE DO nothing END IF UNTIL End-of-file

Modeling Logic with Structured English Read Inventory records WHILE NOT End-of-file DO BEGIN IF IF Quantity-in-stock less than Minimum-order-quantity THEN GENERATE new order ELSE DO nothing END IF END DO Figure shows Structured English representation for Hoosier Burger inventory control system

Example The Hoosier Burger Food ordering system generates two types of usage data, for goods sold and for inventory. At the end of each day, the manager Bob, generates the inventory report that tells him how much inventory has been used for each item associated with sales. The amount shown on the inventory report is used as one input to a large inventory control system Bob uses every day. Consider a Hoosier Burger’s inventory system, which has two sources of data outside the system: suppliers, the food ordering system inventory report.

INVENTORY REPORTS

Example Consider a Hoosier Burger’s inventory system, which has two sources of data outside the system: Suppliers, Stock-On-Hand Supplier provides supplies and send invoices as input to the inventory system, and the system returns payments and orders as outputs to the suppliers. The inventory report from the Customer order system provides the count on how much stock has been used. The processes involved in the inventory system are: Receive and Update the inventory data file as the supplier gives the information about the no. of items supplied, on the invoices. Receive and update the inventory data file as the usage count from the Stock On Hand is received Generate order based on the inventory level obtained from the inventory file and the minimum Order Quantities( which is already stored in the Inventory data file) Generate payment only to those supplier where the supply date is 30 days or greater than today’s date.

50 dozens 5 50 50+5 = 55 25 dozens 25 0+25 = 25 5 cases 10 1 case 1 Items Minimum Order Quantity Quantity Left Quantity added Quantity in Stock = Quantity Left + Quantity added Burgers 50 dozens 5 50 50+5 = 55 Buns 25 dozens 25 0+25 = 25 Straws 5 cases 10 Napkins 1 case 1

Modeling Logic with Structured English Structured English process description mimics the format usually used in programming languages. The filenames are connected with hyphens and the file names and variable names are capitalized. Terms that signify logical comparisons, such as greater than and less than are spelled out rather than represented by arithmetic symbols Structure English specifications are short if they describe lowest level DFD process. Structured English resembles spoken English

Problems with Structured English to represent logic If a process’ logic is complex i.e. if several different conditions are involved and the combinations of these conditions dictate which of the several actions should be taken, then Structured English may not be adequate for representing the logic behind such a complicated choice; rather becomes more difficult to understand and verify. In such cases, a diagram may be much clearer than a Structured English statement.

Modeling Logic with Decision Tables A decision table is a diagram of process logic where the decision logic is reasonably complicated. It is a matrix representation of the logic of a decision Specifies the possible conditions and the resulting actions in a tabular form 9.23

Consider a payroll system, which generates a payroll based on types of employees and number of hours worked. Employees can be of two types Salaried “S” or Hours worked “ H”. Hours worked has three values Less than 40 Exactly 40 More than 40 If an employee is salaried and hours worked <40, pay the base salary. If an employee is hourly based and hours worked <40, pay hourly wage and produce absence report. If an employee is salaried and hours worked =40, pay the base salary. If an employee is hourly based and hours worked =40, pay hourly wage. If an employee is salaried and hours worked >40, pay the base salary. If an employee is hourly based and hours worked >40, pay hourly wage and calculate overtime. There are four possible outcomes (actions) Pay base salary Pay hourly wage Calculate Overtime Produce Absence Report

Modeling Logic with Decision Tables Consists of three parts Condition stubs Lists various conditions relevant to the situation the table is modeling. Action stubs It contains all the possible courses of action that result from combining values of the condition stubs. Rules It is a part of the table that links the conditions to actions. It specifies which actions are to be followed for a given set of conditions 9.25

Figure 9-4 Complete decision table for payroll system example 9.26

Modeling Logic with Decision Tables Indifferent Condition Condition whose value does not affect which action is taken for two or more rules. Rule 5 has the same action as Rule 1 and 3, and governs behavior with regard to salaried employees. The number of hours worked does not affect the outcome for Rules 1,3, and 5. For these rules, hours worked is an indifferent condition in that its value does not affect the action taken. Because of the indifferent condition for rules 1, 3, and 5, we can reduce the number of rules by condensing rules 1,3 and 5 into one rule , as shown in fig 9-5. The indifferent condition is represented with a dash. 9.27

Fig. 9-5 Reduced decision table for payroll system example

Modeling Logic with Decision Tables Standard procedure for creating decision tables Name the condition and all the values each condition can assume Name all possible actions that can occur for different set of conditions List all possible rules : To determine the number of rules, multiply the number of vales for each condition by the number of values for every other condition. In fig 9-4, we have two conditions, one with 2 values and one with 3 values, so we need 2 x 3 or 6 rules. If we add third condition with three values, we would needed 2 x 3 x 3 or 18 rules Define the actions for each rule Simplify the decision table : Make the decision table a simple as possible by removing any rules with impossible actions. Consult users on the rules where the system actions are not clear and either decide an action or remove the rule.

Decision Table – Example 1 Consider a Hoosier Burger inventory reordering function. Reordering depends on number of seasons Academic year Summer Season Spring Holidays Academic Year : When there is an academic season check whether the item is perishable or non perishable. If an item is perishable, such as meat, vegetables, milk etc., the inventory system has a standing daily order with a local supplier stating that a pre-specified amount of food is delivered each weekday for that day’s use and a standing weekend order with a local supplier each Saturday for weekend use. If an item is non perishable, such as straws, cups and napkins, an minimum order quantity is placed when the stock on hand reaches a certain predetermined minimum reorder quantity.

Decision Table – Example 1 Hoosier Burger’s business is not as good during Summer, Christmas and spring break holidays as it is during the Academic year. Summer Season The standing orders with all their suppliers are reduced by specific amounts during the summer i.e. Summer reduction. Holiday Season The standing orders with all their suppliers are reduced by specific amounts during the holiday break i.e. Holiday reduction. Given these conditions, draw a decision table.

Decision Table – Example 1 What can be the conditions: Type of item (P for Perishable and N for Non Perishable) Day of week (D for weekday and W for weekend) Season of year (A for Academic, S for Summer and H for holiday) What can be the possible actions? Standing Daily Order Standing weekend order Minimum order quantity Holiday reduction Summer reduction How many Rules are in this example? 2 x 2 x 3 = 12 Rules

Modeling Logic with Decision Tables

Modeling Logic with Decision Trees A graphical representation of a decision situation Decision situation points are connected together by arcs and terminate in ovals Two main components Decision points represented by nodes Actions represented by ovals Connection between decision points by arcs 9.34

Modeling Logic with Decision Trees Read from left to right Each node corresponds to a condition (choice) The choices are spelled out in a legend for the diagram Each path leaving a node corresponds to one of the options for that choice. From each node, there are at least two paths that lead to the next step, which is either another decision point or an action. Finally all possible actions are listed on the far right of the diagram in leaf nodes. Each rule is represented by tracing a series of paths from the root node, down a path to the next node, and so on, until an action oval is reached. 9.35

Decision tree representation of the decision logic in the decision tables with only two choices per decision point 9.36

Decision tree representation of the decision logic

Deciding Among Structured English, Decision Tables and Decision Trees Criteria Structured English Decision Tables Decision Trees Determining Conditions and Actions Second Best Third Best Best Transforming Conditions and Actions into Sequence Checking Consistency and Completeness 9.38

Summary Several methods of logic modeling Structured English Primarily communication technique for analysts and users Decision Tables Conditions are listed in condition stubs Possible actions are listed in action stubs Rules link conditions with actions 9.39

Summary Decision Tables Decision Trees Lists all possible rules Conditions are portrayed by decision points Values are represented by paths between decision points and ovals that contain actions 9.40

Summary Comparison of Structured English, Decision Tables and Decision Trees Most studies show that decision trees are best for many criteria There is no best technique Analyst must be proficient in all three 9.41