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ITECH7410 Software Engineering Methodologies For Z Notation

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ITECH7410 Software Engineering Methodologies For Z Notation

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ITECH7410 Software Engineering Methodologies For Z Notation

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Course Code: ITECH7410
University: Federation University

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Country: Australia

Questions:
1. Critically analyse and use complex decision making to research and determine the appropriate Software Engineering tools and methodologies to utilize in a given situation2. Apply professional communication skills to support and manage the engineering of a large software system3 Review, critically analyse and develop artefacts to define processes for quality assurance, risk management and communication in large software development projects 4. Implement quality assurance activities in order to verify user requirements and validate design decisions5. Analysis of a large system development problem to decide upon the best methodological approach6. Development of appropriate artefacts to support and manage the software engineering process such as change control and configuration management

Answer:
Introduction:
The software applications developed at present days are consisting of high amount f documentation such as interactive manuals, user guides, documents of design and many more. The Z allows the system engineer to provide a model of the system in the form of mathematical notation that can be used to formalize the idea of documentation requirements (Abad, Noaeen & Ruhe, 2016). The Z-Language is used for creating the notations in z-schema. The Z-Language is formal mathematical language that works on mathematical expressions. The Z-language has various elements like paragraphs, schemas, logic, sets, relations, functions, numbers, sequences and bags.
The article is based on the information of Container Control System using the Z-Schema language. The Z-Notation is created based on the operations of container control system. The initial operations are used for initializing the works.
Initializing Operation:
initTerminal
name: ?
containerStorage: ?
numberOfContainer: ?
ton: ?
 
numberOfContainer ≥ 0
ton ≥ 0 
initDelivery
vehicleNumber: ?
queID: ? 
vehcileIdentifier ≤ 5
queID ≤ 2 
The initialization operations make the system processes initialize. The terminal schema has name, storage, containerNumber and ton attribute. The containerNumber and ton must be greater than 0. The name identifies the name of the container so that system can uniquely identify it during an operation. The Delivery schema is also initialised in this section. The vehicle and que has integral part in delivery. The vehicleIdentifier means number of vehicles are processing current delivery. It should always be less o equal to 5. As this attribute is a Natural number it cannot be negative. These two schemas are the base of all the operations.
Operation 1: Enter_new_container_terminal
initContainerTerminal
containerTerminal 
known = ∅ 
addTerminal
ΔContainerTerminal1
name?: Name
containerStorage?: ContainerStorage
numberOfContainer?: NumberOfContainer
ton?: Ton  
∀i: 1…hwm?name? ≠ names(i)
hwm’ = hwm+1
name′ = names⊕{hwm′ ? names?}
containerStorage′ = containerStorages ⊕{hwm′ ? containerStorage?}
numberOfContainer = numberOfContainers ⊕ {hwm′ ? numberOfContainers?}
ton = tons ⊕ {hwm′ ? tons?} 
This schema is used for recording a new terminal in the container system. It is assumed that the terminal is empty at the beginning of this operation. The known = ∅, means that system does not have any record of container. As the state of the containerControl will change, the system. For each container system, the name, storage, containerNumber and ton are added.
Operation 2: Accept_delivery
acceptDelivery
ΔDelivery1
numberOfVehiclesInQue? : NumberOfVehiclesInQue
vehicleNumber? : VehicleNumber 
∀i: 1…hwm?VehicleNumber? ≠ vehicleNumber(i)
hwm′ = hwm +1
currentLoad ≤ ton – containerStorage
numberOfContainer ≤4
⇒(vehicleNumbers′ = VehicleNumber ⊕ {hwm′ ? VehicleNumber })
numberOfContainer = 5
⇒ (numberOfVehiclesInQue ′ = numberOfVehiclesInQue +1) 
The dynamic operations starts from here. The container control system will start checking predefined conditions. The system will check if quantity of vehicle working for loading is less than 5 or not. If the number is 5 then the system will add the new delivery request to que along with the vehicle id. If the number of vehicles is less than 5 then the vehicle will be assigned for loading container.
Operation 3: Accept_pickup
acceptPickup
ΔDelivery1
vehcileIdentifier? : VehicleNumber
companyID? : CompanyID
qty? : Qty
tons? : Tons 
∀i : 1…hwm?VehicleNumber? ≠ VehicleNumber(i)
hwm′ = hwm +1
currentLoad ≤ ton – containerStorage
numberOfContainer ≤4
⇒(vehicleNumbers′ = VehicleNumber ⊕ {hwm′ ? VehicleNumber }
Tons′= Loads ⊕ {hwm′ ? Tons}
companyID′ = companyID ⊕ {hwm′ ? companyID }
qty′ = qty ⊕ {hwm′ ? qty}
currentLoad′ = currentLoad ⊕ {hwm′ ? currentLoad })
numberOfContainer = 5
⇒ (numberOfVehiclesInQue ′ = numberOfVehiclesInQue +1
Tons′= Loads ⊕ {hwm′ ? Tons}
companyID′ = companyID ⊕ {hwm′ ? companyID }
qty′ = qty ⊕ {hwm′ ? qty}
currentLoad′ = currentLoad ⊕ {hwm′ ? currentLoad }) 
The pickup accept is the next phase of delivery operation. This operation will change the state of delivery process. The attributes like vehicleIdentifier, frieghtCompany, quantity and ton are used in this operation. The whole process is centric to vehicle identifier. If the number is 5 then the system will add the new delivery request to que along with the vehicle id. If the number of vehicles is less than 5 then the vehicle will be assigned for loading container. The system will calculate the current load. The system will also check if the current load is less than or equal to available storage in the container.
Operation 4: Leave_delivery_queue
leaveDeliveryQueID
ΔqueID1
vehcileIdentifier? : VehicleNumber
waitingTime?: WaitingTime
preferredWaitingTime? : PreferredWaitingTime
error!: ? 
preferredWaitingTime ≤ waitingTime
⇒(numberOfVehiclesInQue′ = numberOfVehiclesInQue – 1)
numberOfVehiclesInQue′ = ∅
⇒ error = No truck available in queID 
The driver will leave delivery que of waiting time is more than preferred time. As each truck has only one driver, the system will consider the driver as vehicle for data integrity purpose. The system will also show, the error message of the que is empty.
Operation 5: Unload_Ship
unloadShip
ΔcontainerTerminal1
qty?: X
ton? : Y
error!: Report  
qty?* ton? ≥ containerStorage
⇒ error!= no space available
qty?* ton? ≤ containerStorage
⇒(containerStorages′ = containerStorages ⊕ {hwm′ ? qty?* ton? }) 
The vehicles does the job of unloading the ships. The system calculates which vehicle is unloading which container and how much amount of goods are unloaded. The system will calculate the amount of product by multiplying the quantity with ton. The storage is also updated when the vehicle unload the ship.  
Operation 6: Container_terminal_account
findComntainerTerminalAccount
ΞcontainerTerminal1
startDate! : Date
endDate! : Date
companyID? : CompanyID
qty? : Qty
tons? : Tons 
companyID? ∈ known
Date! = endDate!- startDate!
Date! = containerTerminal(companyID?, qty?, tons?) 
Find container terminal account does not change the state of operation. The data find in the operation will be restricted by two dates. The operation will identify the amount of product delivered by a freightCompany within given deadline. The user of the system will enter the deadlines.
Operation 7: Ships_total_account
findShipTotalAccount
ΞcontainerTerminal
name! = Name
qty? : Qty
tons? : Tons 
name? ∈ known
name! = containerTerminal(qty?, tons?) 
The shipment account is identified using the name of the container, quantity and ton. The name of the container must be known. The system must find the storage of the container based on the name of the container.
Operation 8: Freight_company_account
findCompanyIDAccount
ΞcontainerTerminal
name! = Name
companyID? : CompanyID
qty? : Qty
tons? : Tons
count1!: X
count2!: Y 
companyID? ∈ known
qty?* ton? ≤ count1
qty?* ton? ≥ count2
companyID! = containerTerminal(qty?, tons?) 
Finding the fright company does not also change the state of Delivery. The system finds how much amount of products are delivered by the freight company from beginning. The system first checks the freight company name.
Conclusion:
The above study concludes that the system will effectively handle the process of the container control system. The system will handle all the operations properly. The system will generate proper error reports when predefined metrics are not met. The specification statements looks similar to each other. It is because a specific notation pattern has been followed for describing the schema of each state.
Bibliography:
Abad, Z. S. H., Noaeen, M., & Ruhe, G. (2016). Requirements engineering visualization: a systematic literature review. In Requirements Engineering Conference (RE), 2016 IEEE 24th International (pp. 6-15). IEEE.
Iqbal, M. Z., Arcuri, A., & Briand, L. (2015). Environment modeling and simulation for automated testing of soft real-time embedded software. Software & Systems Modeling, 14(1), 483-524.
Klein, M. J., Sawicki, S., Roos-Frantz, F., & Frantz, R. Z. (2014, April). On the Formalisation of an Application Integration Language Using Z Notation. In ICEIS (1) (pp. 314-319).
Klein, M. J., Sawicki, S., Roos-Frantz, F., & Frantz, R. Z. (2014, April). On the Formalisation of an Application Integration Language Using Z Notation. In ICEIS (1) (pp. 314-319).
Spivey, J. M., & Abrial, J. R. (1992). The Z notation (p. 90). Hemel Hempstead: Prentice Hall.
Zamli, K. Z., Alkazemi, B. Y., & Kendall, G. (2016). A tabu search hyper-heuristic strategy for t-way test suite generation. Applied Soft Computing, 44, 57-74.

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