1. By DrinkableMilk 10.29.2008

2. Group Members Chen Qiushi Cen Yunsi Wu Lezhen Lin Yanmei Zhang Chen Zeng Ting

3. Agenda

4. Agenda

5. Task ▫A ▫A Milk Supply Chain ▫Different ▫Different Roles  Manager(=Plant),  Manager(=Plant), customer, and farmer ▫Interactions ▫Interactions Between Roles:  Ordering,  Ordering, supplying, producing milk… ▫Sequences ▫Sequences Exist Between Functions

6. Details of Sequences 0. Login in different roles 1. Customer orders some milk to a certain plant 2. Milk plant calculates the volume of milk 3. Milk plant asks milk farmer to supply milk 4. Milk farmer takes time to deliver his milk to milk plant 5. Save the processes above Done!

7. Agenda

8. Task :A Milk Supply Chain ▫Different ▫Different Roles  Manager(=Plant), customer, and farmer ▫Interactions ▫Interactions Between Roles:  Ordering,  Ordering, milking, order processing … ▫Sequences ▫Sequences Exist Between Functions Customer Manager Farmer Milking Ordering Order Processing Login

9. Sequences of functionSequences of function 0. Login in different roles 1. Customer orders some milk to a certain plant 2. Milk plant calculates the volume of milk 3. Milk plant asks milk farmer to supply milk 4. Milk farmer takes time to milk and deliver his milk to milk plant 5. Save the processes above Done!Done! Customer Login Plant Farmer Finishing Milking Ordering OrderToFarmer OrderToPlant Report Milk Processing Initial

10. Customer Login Plant Farmer Finishing Milking Ordering OrderToFarmer OrderToPlant Report Milk Processing Initial

11. Process Model A model with a set of entities and a set of activities scheduled according to particular sequences and particular constraintsA model with a set of entities and a set of activities scheduled according to particular sequences and particular constraints

12. Process Model Design

13. Detailed Process Design ▫Functions ▫ parameters ▫return values… Function Name DescriptionInput parameters Return values… MilkCowGet milk from cows Cow's ID, farmer's money volume of milk HealCowImprove cow's health state cow's ID, heal method Cow's health state level …

14. Process Model Design Function Name DescriptionInput parameters Return values… MilkCowGet milk from cowsCow's ID, farmer's money volume of milk HealCowImprove cow's health state cow's ID, heal method Cow's health state level …

15. Model Design Tools Flow chart Petri net OPN From www.wikipedia.com From www.baidu.com

16. A network of objects and processes connected by relationships, so called OPN(Object - Process - Network) OPN Object Process

17. Farmer Milking Milk

18. Token's key/value Farmer_IDCredit... 1100...

19. Process:do operations Farmer_IDCredit... 1100... Farmer_IDCredit... 190... Farmer_IDCreditMilk_Time... 1900...

20. Conditions:control the flow Farmer Credit>85 Milking Farmer_IDCreditMilk_Time... 1900...

21. Synchronization Farmer Milking Order to Farmer Order to Farmer

22. OPN is not only a descriptive model language, but also an executable model language. Follow this fashion, we specify operations and conditions of the problem. Next we will construct our data model.

23. Agenda

24. Data Model  Definition  Categories  Data model Design

25. Data Model A collection of conceptual tools for description. It describes data, data relationships, data semantics, and consistency constraints. ——From our textbook

26. Based on the application of different levels

27. Data Model Categories

28. Data Model Design

30.  Data model comes from the process Data Model Design Two methods for conceptual design Data dictionary E-R model

31.  Data Dictionary is a collection of all elements of the process model. It consists of many entries Data Model Design(1) An entry consists of: Name Data description Data source Data type Design constraint Others

32. NameDescriptionSource··· farmer A person makes money by providing milk··· Login··· Stock Order milk, send complaints ··· plant or farmer ··· Order The storage is related to orders··· custome r ··· An simple dictionary Especially when the size of data set becomes larger.

33.  ER-Model Data Model Design(2) Customer Plant Farmer MilkOrder Plant_ID Loc_x Plant_ID Loc_x Loc_y Name Loc_y Plant_ID Name Loc_y Loc_x  Entity sets  Relation sets  Attributes

34. Customer Plant Farmer MilkOrder Plant_ID Loc_x Plant_ID Loc_x Loc_y Name Loc_y Plant_ID Name Loc_y Loc_x E-R model is a kind of conceptual design.

35. Data Model Design(3)

36. Relational Design  Reduce redundancy  Losslessness  Dependency preservation

37. Normalization First Normal Form Second Normal Form Third Normal Form Boyce-Codd Normal Form Data Model Design(3)

38. Our achievement

39. Procedures After Design…

40. Agenda

41. Testing is the process of executing a program with the intent of finding errors. —— 《 The Art of Software Testing 》 Glenford J. Myers Definition Of Testing

42. Procedure Of Testing

43. A test case is a set of test data for the program——data the program must handle correctly to be considered a successful program (Smallest component element of source code ) Design of test case  Black-Box Testing Also data-driven, or input/output-driven testing  White-Box Testing Also logic-driven testing Test Case

44. DrinkableMilk.m (*This function gets the value of a certain key in a certain token. @input:token,key @output:value of the key *) GetTokenValueByKey[token_, key_] :=Block[{valuePosition}, valuePosition = Position[token[[5]], key]; If[valuePosition == {}, Return[Null], Return[Delete[token[[6, Delete[valuePosition, 0]]],0]] ]; ] What we’re only concerned with Unit Testing Using Munit(1/2)

45. DrinkableMilk.mt token = { “”, “”, { “type”, “number”, “time”, “price”, “customer” }, { "A", "1", "3", "10", "B“ } }; Test[ GetTokenValueByKey[token, "number"] ‘ "1“ ‘ TestID->"DrinkableMilk-20081026-Q0Z1O9" ] Key Value Judgement:( if in Java language :) AssertTrue(GetTokenValueByKey[token, "number"] ==1”) Unit Testing Using Munit(1/2)

46. 46 Obje ct PreconditionProcessPostcondition Objec t * “OrderAmount ”>5 OrderProcesso r “CustomerMoney ” Decreases by 5×unit price * precondition GetTokenValueByKey[token,“Order Amount“] Postcondition GetTokenValueByKey[token,“OrderA mount“] How to test pre/post conditions

47. SaveIntoDB _Finish

48. System testing Database Before Running Print out the Running Result (in computer memory) Database After Running

49. Comparison Results: Get["DrinkableMilk`DrinkableMilk`"]; RunGraph["1",OPNGraph,200,PR® True]; Barrierlogin {355118,0,{Iss,Pre-1},{275854},{},{}} 0 BarrierProcessing {979397,0,{Plant,Pre-4},{877581},{tokenType,plantID,volume,locX,locY},{PLANT,2,15.0,45.0,81.0}} 0 BarrierProcessing {554280,0,{OrderToPlant,Pre- 3},{263933},{customerID,demand,farmerID,locX,locXC,locXP,locY,locYC,locYP,need,plantID,tokenType,totalTime},{5,23,NULL,21.,NU LL,NULL,21.,NULL,NULL,NULL,NULL,ORDER,NULL}} &&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&7 0 BarrierMilking {563776,0,{Farmer,Pre-6},{711},{tokenType,farmerID,speed,locX,locY},{FARMER,4,14.0,65.0,43.0}} BarrierProcessing {554280,0, {OrderToPlant,Pre3},{263933}, {customerID,demand,farmerID,OrderID, plantID,totalTime}, {5,23,4,69,2,35399200}}

50. New Tuple added

51. Agenda

52. Background: Application of Dairy Farm System Whole process from design to development ▫Step 1:  Client v.s. DrinkableMilk Development Group (DDG)  Client puts forward their demands Review

53. ▫Step 2:  DDG deals with the demands  Build up conceptual process model ▫Step 3: design the detailed process model  Functions, parameters, return values…  DDG will generate a … ▫Step 4: Data Model Design (ER Model)  Establish conceptual Model and optimize using… ▫Step 5: Mapping to Relational data model

54. Process model (NET) Activities(NODE) Int CalculatingTime() Int CalculatingDist() … Functions (DETAILS) Client’s Demand Client’s Demand

55. Process+Data Model Activities Functions

56. ▫Step 6: Implementation and Unit test  Independently  Separately ▫Step 7: Integration test & System test Review

57. Miserable experience before ▫Coding without thinking before ▫Unclear steps for working on a project. A new method ▫Process Model and Data Model ▫Design and Development Begin with Process in mind

58. THANKS ▫By DrinkableMilke Group ▫2008-10-29