Cloud Computing And Healthcare: An Analysis Of Non-Functional Requirements And Development Methods

Non-Functional Requirements

Question:

Discuss about the Systems Development Life Cycle Methodology.

Cloud computing has received a lot of attention recent years because to the efficiencies and conveniences it provides to business management. In essence, its service extends the availability of information which is a crucial component of the decision-making process. However, despite its widespread application its functionalities and concepts are still not clearly understood by the users. In all, cloud computing offers subscription-based resources and services to users through publicly networked infrastructure (CSCC, 2016). This infrastructure is usually set up by the internet which has a higher reach of the consumers owing to its extensive connectivity. As an organization seeking to better its service delivery structure, Headspace aims to incorporate the resources of cloud solutions where patient’s data will be adequately stored and accessed. Therefore, this report analyzes the various aspects of cloud computing including the security and data ownership requirements (CSCC, Security for Cloud Computing Ten Steps to Ensure Success verison 2.0, 2015). Moreover, the report also highlights the development process of the proposed system and the related non-functional requirements.

In system design, the overall requirements come from the system’s stakeholders and users who demand certain functionalities as well as preferences. From these demands, the developers will analyze and provide consistent requirements based from the raw descriptions. Now, non-functional requirements describe the “how’’ and not the “what” the system can do. Therefore, they will dictate how the system performs certain roles (Kotonya & Sommerville, 1998). Furthermore, unlike functional requirements, they are difficult to test and will only be evaluated using subjective analysis. In general, they are:

• Understandability- where the features of the system usability, modifiability and customizability affect the interaction with the users.
• Adaptability- which is based on the ability of the system to provide various functions depending on the user requirements. This feature also dictates the system’s performance.
• Robustness – the system must be reliable so as to incorporate all functionalities and user platforms including system attacks.
• Integrity and security – the resources used must be protected from unauthorized access(Beauchamp, 2009).

These are the factors that affect the system’s run-time behaviour, user’s interaction and the overall package design (Informations, 2012). In this case, we highlight the following elements:

• Conceptual integrity – a key element of the system’s security more so, because it is set to be integrated with a public infrastructure (cloud).
• Maintainability – the user should transition from one system feature to another with ease.
• Supportability – finally, as a reliability feature, the system should offer guidelines to manage faults and issues(Microsoft, 2017).

In general, an interface will highlight a common boundary that separate systems that exchange information. In this case, two system exists, the proposed Headspace system and the cloud facility. Furthermore, there is the user interface which will deliver the final solutions and data to the end users (overflow, 2017). Now, all these elements should deliver services to the users using the following attributes (system and UI features):

• Simplicity – the system’s usability will depend on the ability of the user to perform their duties with ease.
• Conciseness and clarity – furthermore, each operational elements such as a button or icon should be clearly outlined to promote the performance of the system.
• Interoperability – i.e. the interfaces must be compatible with a wide range of operating system and deployment platforms(Capes, 2011).

These are elements that will limit the design of the system, they include manufacturing technology as some users will demands features not accessible to others and the overall design budget. In all, these factors will limit the final solutions within their existing conditions (CSSE).

Design Constraints

Cloud-based solutions are considered for this application since they will extend the application of the proposed system by increasing its availability and accessibility (CSCC, Practical Guide to Hybrid Cloud Computing, 2016). However, with these resources, the system will also face some drawbacks as highlighted below.

• First, the cost of designing and implementing the system will be substantially minimized because the end user will not cater for the foundational infrastructure. In essence, resources such as storage, networks and processors will be leased from the service provider.
• Secondly, the resources will be readily available to the users after being hosted online through the resources of the cloud. This outcome will also increase its accessibility.
• Moreover, the system resources (Headspace application) will become more robust as several backup options will exist as provided by the cloud infrastructure. Therefore, in case of disasters, the user will just access different servers or resources as supported by the service provider(Dignan, 2016).

• Cloud solutions offer end users minimal system control because they host resources in foreign environments and use unknown technological features. Due to this limitation, the users cannot adequately account for their resources.
• Data security and privacy is another substantial weakness as the user trust a third party member with their sensitive data. Furthermore, a public infrastructure is used to convey the data between the parties involved. This outcome raises some serious concerns which in most cases limit the application of the technology(Gadgetzz, 2012).

Cloud storage facilities operate within the digital platform which unlike the physical world is not adequately governed by legal stipulations. Therefore, when adopted, the third party resources will not be governed by the Australian law, which will require other additional measures to protect the data involved. Therefore, as a solution, the Headspace project must first identify a competent service provider with verifiable security standards (CSCC, Security for Cloud Computing Ten Steps to Ensure Success verison 2.0, 2015). Thereafter, the organization should request a proper service agreement detailing the ownership of the data in use. Moreover, the channels of communication between the project and the service provider should be properly encrypted using advanced protocols e.g. end to end encryption. Finally, all users accessing the system must be authenticated and verified based on a predefined access policy.

Software or system development life cycle (SDLC) stands for the conceptual model that is usually applied in the implementation of information systems. In essence, SDLC follows a project management outline where specific developmental stages are used to facilitate the design and deployment of a software package. Now, as its common today, most systems will have different functionalities and requirements which is also usually reflected in the design process where a number of development procedures (methods) are exhibited (Barracliffe, Gardner, Hammond, & Duncan, 2009). Examples of these methods include; predictive SDLC which has models such as the waterfall model and adaptive SDLC which has agile models.

This method generally assumes that the development stage of the system can be predicted and outlined with the utmost accuracy. Furthermore, the approach will assume all the phases of system implementation following a thorough documentation of the requirements. In addition to this, the phases of the system development will follow a sequential structure where each and every stage is executed independently with minimal overlaps. Therefore, each stage must fulfil its requirements before a signoff is given to proceed to the next stage (MIS, 2014).

• Due to its precise procedure, the predictive approach is easy and simple to use.
• Moreover, the approach has minimal resource requirements as they are adequately outlined in the initial assumptions.
• Furthermore, it is possible to predict the timeline of the system development.

• First, the approach is very rigid and does not adapt to any change.
• Secondly, the method facilitates several instances of uncertainty more so, when unknown variables are introduced into the system design.
• Finally, the method uses a lot of time to implement a single solution as the development phases must be implemented sequentially without any overlaps.

Unlike the predictive approach that makes all the assumptions at the beginning of the project, the adaptive approach will provide room for system changes by creating a dynamic implementation process. Therefore, any variations in the project’s scope are adequately adopted into the design including changes in personnel, system priorities and requirements (MIS, 2014). Furthermore, to deal with the uncertainty of system changes, the approach breaks down the entire process into smaller subsections which are then implemented concurrently to yield the final system. Moreover, the final system is deployed using iterative procedures which assemble the final solution.

• First, it’s an agile approach that can adapt to any change.
• Secondly, it’s time efficient as the implementation stage are executed simultaneously.
• Finally, it focuses on the needs of the user which improves the system’s usability and performance.

• Unlike the predictive approach, its resource intensive owing to the extended requirements of each development stage.
• Secondly, it requires a lot of expertise to implement solutions.

Cloud Computing and Healthcare

From the description that is given above, the predictive method is suitable for simple projects that have minimal requirements. On the other hand, the adaptive method is seen as a solution for all applications as it caters for all uncertainties. Now, the project at hand already contains a lot of uncertainties, from the unknown cloud service provider to the development process itself. Furthermore, the system requirements may change from time to time owing to the field of application which has many users. Therefore, the adaptive approach offers the best solution for implementing healthcare system (CSCC, Security for Cloud Computing Ten Steps to Ensure Success verison 2.0, 2015).

Conclusion

Cloud computing is rapidly taking over the digital industry because of its extensive benefits and conveniences. In all, a user can access multiple resources that previously were either unavailable or unaffordable. Furthermore, the user can optimize the available resources by applying the flexibility and scalability features of the cloud services. Now, these benefits and application will boost the services of Headspace since it will be able to store and access patient’s records in spite of the practitioners’ location or identity. Moreover, it will improve its service delivery structure since the users will perform their roles using any given device or platform.

References

Barracliffe, M., Gardner, L., Hammond, J., & Duncan, S. (2009). Systems Development Life Cycle (SDLC) Methodology. Information Technology Services, Retrieved 03 October, 2017, from: https://its.ucsc.edu/drb/sdlc/documents/sdlc-handbook-reduced.pdf.

Beauchamp, G. (2009). Non functional requirements. Retrieved 03 October, 2017, from: https://www.smart-ba.com/articles/Non%20functional%20requirements.pdf.

Capes, T. (2011). User Interfaces in Computing. Retrieved 03 October, 2017, from: https://www.cs.toronto.edu/~capestim/csc104/csc104s11/UserInterace.pdf.

CSCC. (2015). Security for Cloud Computing Ten Steps to Ensure Success verison 2.0. Cloud Standards Customer Council, Retrieved 03 October, 2017, from: https://www.cloud-council.org/deliverables/CSCC-Security-for-Cloud-Computing-10-Steps-to-Ensure-Success.pdf.

CSCC. (2016). Practical Guide to Hybrid Cloud Computing. Retrieved 03 October, 2017, from: https://www.cloud-council.org/deliverables/CSCC-Practical-Guide-to-Hybrid-Cloud-Computing.pdf.

CSSE. (n.d.). Design Constraints. Software Engineering Design , Retrieved 03 October, 2017, from: https://teaching.csse.uwa.edu.au/units/CITS2220/lecturenotes/lec09.designconstraints.pdf.

Dignan, L. (2016). Public cloud computing vendors: A look at strengths, weaknesses, big picture. ZDNet, Retrieved 03 October, 2017, from: https://www.zdnet.com/article/public-cloud-computing-vendors-a-look-at-strengths-weaknesses-big-picture/.

Gadgetzz. (2012). Strengths and Weaknesses of Cloud Computing in your Business. Retrieved 03 October, 2017, from: https://gadgetzz.com/2012/07/23/strengths-and-weaknesses-of-cloud-computing/.

Informations. (2012). 3 Essential qualities of information systems. Retrieved 03 October, 2017, from: https://infomotions.com/musings/tricks/manuscript/1500-organizing.html.

Kotonya, G., & Sommerville, V. (1998). Non-functional Requirements. Requirements Engineering Processes and Techniques, Retrieved 03 October, 2017, from: https://www.csm.ornl.gov/~sheldon/cs531/ch8.pdf.

Microsoft. (2017). Chapter 16: Quality Attributes. Design fundamentals, Retrieved 03 October, 2017, from: https://msdn.microsoft.com/en-us/library/ee658094.aspx.

MIS. (2014). The System Development Life Cycle. Retrieved 03 October, 2017, from: https://utexas.instructure.com/courses/1166782/files/38198507/download.

overflow, S. (2017). Software Requirments Specification (SRS): What are ‘System Interfaces’? Retrieved 03 October, 2017, from: https://stackoverflow.com/questions/25728822/software-requirments-specification-srs-what-are-system-interfaces.