Three methods can be used for the collecting the data required for use case development. The use case is referred to as the interaction diagram. In order to develop the diagram, the analyst need to have data regarding interaction of the users with the system. Three methods that will be used are focus group, surveys and interviews.
Focus Group: The focus group is the technique of exploring opinions of the users regarding the IT product (Lopes 2016). Taken as an example, application development of system for car parking system within the city council of Shire city. In the region of system-use interaction, this method is used for identifying the perspective of the user along with the usability. However, the focus group method is not very suitable for identifying and determining usability. It though provide an idea regarding what the users in a group thinks about the idea and scope of the system. This tool is prevailing for development of system. It is not the only method that allows the analyst to gather all the data regarding the human-system interaction or use case diagram.
Surveys: Among the analysts, this method is mostly known as the basic types of quantities research. The survey sampling becomes useful for the development of use case diagram whilst the quantity of interest is huge or detached a large geographic region. In order to gather feedback and attitude of the potential user in terms of human-computer interaction (Lazar, Feng and Hochheiser 2017). The potential users of the car parking system will be residing in a large geographical region. The survey will be able to collect a large amount of data from the users of Shire City car parking system through doing various online services. The survey will be like for how much time a person would want to park a car, which facilities they intend to have at the parking are and many more. The surveys and questionnaires are complimentary tools. The questionnaire will be comprised of questions that will be created with the purpose of getting the system usability related data. Questionnaire will be a part within the survey process.
Interviews: Interviews with interviewees’ assent, by making inquiries that investigate an extensive variety of worries about an issue, to give them the opportunity to give definite reactions. Interviews were utilized as a part of any period of the venture, from beginning investigation to prerequisites gathering, assessment of models, and summative assessment of finished systems. Interviews were connected to every one of the ventures (Lopes 2016). On account of task 3, interviews took after the survey to supplement the assembled information. At the point when the interviews were finished up another stage began, too information interpretation and investigation.
Figure 1: Use Case Diagram of Shire Free Council Parking System
(Source: Created by Author)
Use Case ID |
Primary Actor |
Use Cases |
UC-1 |
Attendent |
Manual Control Gate |
UC-2 |
Sensors |
Detect Vehicle |
UC-3 |
Car |
Car Identification |
UC-4 |
Printer |
Print ticket and reports |
Use Case ID: |
UC-1 |
Use Case Name: |
Print ticket and reports |
Created By: |
Enter your name and student ID |
Date Created: |
January 4, 2017 |
Actors: |
There are two categories of actors such as primary and secondary Primary Actors – · Printer · Sensor Secondary Actors – · Car · Attendant |
Description: |
At the point when the auto enters the parking part it actuates the passage sensor and alternate sensors associated in the system. The tag is examined by the smaller scale sensor camera and data with respect to the distributed parking space is put away in the database of the data framework. Each of the parking space are introduced with a micros sensor for detecting the free or possessed space and the data is refreshed in the database at a consistent interim of time. The season of passage ought to likewise be recorded for the computation of the time furthest reaches of each of the vehicles. The printer is connected to the system and when the system informs the printer to print a ticket, it generates one. |
Trigger: |
The printer will be generating tickets against the parking of individual persons. |
Preconditions: |
There are a set of assumptions that must be true in order to print a ticket. Step#1: The car is present at the barrier and Step#2: The system finds an available space in the parking lot Step#4: The attendant allows the car to enter Step#3: The car reaches the ticket generating space |
Postconditions: |
The small scale camera sensor ought to be associated in the data framework and when the auto lands at the parking space the data framework ought to be refreshed at a constant from empty to possess. The auto number plate is examined and the points of interest of the vehicle are included the database. After substantial authorization of the auto the auto can enter the auto parking framework. A message is displayed in the display screen with the section time and the points of interest of the auto. The ticket is provided to the owner of the car. |
Normal Flow: |
At the point when the auto approaches the barrier of the auto parking framework the miniaturized scale sensor camera filters the number plate and stores it in the database alongside the time. A message is displayed with the subtle elements of the auto and the accessible parking space to the clients. The auto enters the parking parcel and possesses the space and the database is refreshed. The sensors introduced in the parking space detects the auto and on expiry of the session sends message to the data framework. At the leave barrier the data of the auto is rechecked and coordinated with the data put away in the database for fruitful approval and the barrier is raised. Ticket is generated after the system instructs. |
Alternative Flows: [Alternative Flow 1 – Not in Network] |
The barrier will not be opened for the person if the data is not matched with the stored information in the system. |
Exceptions: |
The main issue can be that the printer is not working. |
Includes: |
NA |
Frequency of Use: |
Various times a day |
Special Requirements: |
The requirement of the project can be classified into functional and non-functional requirements and given below: Functional Requirement Scanning: The system will be scanning the license plate for generating tickets. Database: The database will be holding all the information that are required for executing the processes of the business. Authorization: The ticket must be valid and after the ticket is authorized, the owner will be able to take his/her car. Printing: Tickets will be generated with the information of the space taken, amount to be paid and license number of car. Non-Functional requirement Security: The system will be holding the sensitive information related the parking process. The system, if successfully attacked by criminals, will be malfunctioning. Scalability: Not every day or month the amount service seekers will be of same amount. The system should be smart enough to use resource based on the service need to be provided each day or month. Availability: The system will be on and running from morning to night. If any small issue occurs then the system maintenance process will be done after providing service is stopped at night. Real-time data flow: It is essential that the system uses the method of real time dataflow within it. It will result into less amount of errors in finding available free parking spaces. |
Assumptions: |
For the development of the information system the following assumptions are made such as: · The instruction and the display messages are shown in English and the user understand the language for using the information system · The owner of the system uses authorization for using the system · All the information of the vehicles are stored in the information system securely. |
Notes and Issues: |
If the printer gets damaged then an additional printer for temporary use must be available to the parking region. |
References:
Bryman, A. and Bell, E., 2015. Business research methods. Oxford University Press, USA.
Hajri, I., Goknil, A., Briand, L.C. and Stephany, T., 2015, September. Applying product line use case modeling in an industrial automotive embedded system: Lessons learned and a refined approach. In Model Driven Engineering Languages and Systems (MODELS), 2015 ACM/IEEE 18th International Conference on (pp. 338-347). IEEE.
Hayes, A.F. and Preacher, K.J., 2014. Statistical mediation analysis with a multicategorical independent variable. British Journal of Mathematical and Statistical Psychology, 67(3), pp.451-470.
Jha, P., Jena, P.P. and Malu, R.K., 2014. Estimating software development effort using UML use case point (UCP) method with a modified set of environmental factors. International Journal of Computer Science and Information Technologies, 5(3), pp.2742-2744.
Lazar, J., Feng, J.H. and Hochheiser, H., 2017. Research methods in human-computer interaction. Morgan Kaufmann.
Lopes, A.G., 2016. Using research methods in human computer interaction to design technology for resilience. JISTEM-Journal of Information Systems and Technology Management, 13(3), pp.363-388.
Mertens, D.M., 2014. Research and evaluation in education and psychology: Integrating diversity with quantitative, qualitative, and mixed methods. Sage publications.
Mondal, B., Das, B. and Banerjee, P., 2014. Formal Specification of UML Use Case Diagram-A CASL Based Approach. International Journal of Computer Scienceand Information Technologies, 5(9), pp.2113-2717.
Nassif, A.B., Capretz, L.F. and Ho, D., 2016. Enhancing use case points estimation method using soft computing techniques. arXiv preprint arXiv:1612.01078.
Rautaray, S.S. and Agrawal, A., 2015. Vision based hand gesture recognition for human computer interaction: a survey. Artificial Intelligence Review, 43(1), pp.1-54.
Rhazali, Y., Hadi, Y. and Mouloudi, A., 2014. Transformation method CIM to PIM: from business processes models defined in BPMN to use case and class models defined in UML. International Journal of Computer, Electrical, Automation, Control and Information Engineering, 8(8), pp.1453-1457.
Yue, T., Briand, L.C. and Labiche, Y., 2015. aToucan: an automated framework to derive UML analysis models from use case models. ACM Transactions on Software Engineering and Methodology (TOSEM), 24(3), p.13.
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