Discuss About The Software Development Lifecycle Computing?
According to many technology experts, cloud computing represents the next generation of information technology where computing resources and services will be offered online through the internet infrastructure. This notion seems to come from the diversity that cloud-based solutions offer more so, their accessibility levels. In essence, as a subscriber of cloud resources, a user can access all IT resources at the touch of a button without establishing any form of infrastructure. Therefore, resources such as storage, networks and servers can be applied into different functionalities at minimal costs (Velagapudi, 2012). Now, consider the project at hand, where Headspace a healthcare organization aims to boost its data management procedures by developing a modern information system. Now, this system should also be able to provide the medical personnel in the institution with information at any given location which necessitates the application of cloud services. In the end, this report highlights these requirements of the Headspace project including the development methods.
First, what are the functional requirements? These are system elements that determine the operations and functionalities of the designed system. Therefore, they are directly related to the system’s specifications. On the other hand, the non-functional requirements set the criteria for judging the system’s performance particularly, its interaction with the end user (Chung, 2012). So, the non-functional requirements serve as operational constraints because they limit system functionalities based on user preferences and requirements.
To highlight these features, one must analyze the system as an end user having the end product at hand without the technical considerations. Therefore, the overall attributes of the system define the system’s qualities, which are:
As an end user, the system’s visual system plays a key role in determining the system performance i.e. its suitability and usability. Therefore, the system may have the best functionalities but poor interfaces will limit its application because the users have minimal interactions with it (Kathuria, 2011). The following requirements are important for the interface of the project:
These are the limitations that will restrict the overall freedom of developing and using the system, they are:
Cloud-based solutions offer a different view to computing resources by extending the foundational element of IT beyond those of the physical environment. In essence, the computational resources such as storage are moved to a virtualized platform which increases their accessibility and availability. Now, these benefits also extend the financial resources beyond their basic application because the users do not need to establish the foundational structures of the technology (Council, 2017). Therefore, by using cloud computing, data management become easier because the end user only performs the front-end roles of making decisions after accessing the final data that is already analyzed by the online infrastructure. Similarly, the Headspace project will attain similar benefits if it adopts the cloud facilities. In all, the following strengths and weaknesses will be exhibited with cloud resources:
SDLC defines an approach of implementing a software solution, this approach follows a logical flow of events serving the different system requirements and functionalities. Therefore, a sequential procedure accurately defines the true meaning of SDLC (Utexas, 2017). At the same time, different systems will perform different functionalities as dictated by their development requirements. These differences outline the various approaches used to implement different solutions or system packages. In this case, two such methods are highlighted; predictive SDLC and adaptive SDLC.
This approach is characterized by a pre-determined procedure where all the system’s variables and assumptions are outlined before the implementation process. Furthermore, all the development stages and steps are pre-defined which provides the developers with a concise design procedure. In addition to this, the approach does not change the parameters of implementation after the process commences. In fact, any adjustments to the system are met by a rigid system that can only be restarted to accommodate them. Nevertheless, the development stages of the predictive approach are conducted sequentially having each stage following the other, for instance, the testing phase will only occur after the deployment stage (Applitude, 2011). Now, a good example of the predictive approach is the waterfall model which follows a concise and sequential procedure having the following stages: Initiation, planning, design, building, testing and deployment.
An approach that follows an agile and dynamic procedure to system implementation having established the system’s parameters. Therefore, unlike the predictive approach which does not respond to changes, the adaptive method operates with an open mind for variations and systems adjustments. Moreover, the approach does not follow a sequential procedure where each stage depends on the other. Instead, all development stages exist independently having their own requirements. Now, because of this outcome, the approach will divide its implementation procedures into several stages which are run concurrently and are only combined after they meet their outlined objectives (Gupta, 2014). For this function (stage collaboration), several iterative techniques are used to combine and test the final solution, functionalities that perfect the final system.
The Headspace project has very many variables and requirements to consider which limits the predictability of the first approach. Secondly, its integration with cloud computing will force it to have consistent changes which again cannot be accommodated by the predictive method. However, the adaptive method checks all the boxes of the project at hand, having resilient and flexible procedures (Feher, 2013). In all, the adaptive method will optimize the solution by employing a user-centred design and by employing specific specialists for each requirement.
Cloud resources extend the benefits of virtualization into data management through the conveniences of resource flexibility, mobility and scalability. Moreover, they minimize the overall user expenditures by facilitating the access to IT resources through leased models. Now, the Headspace project requires similar benefits so as to extend its functionalities beyond the existing physical infrastructure. In addition to this, its virtual system collaboration can only be met by applying an agile approach into its development process, an outcome that can only be met by the adaptive SDLC method.
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Applitude. (2011). Plan-driven versus Agile = Predictive versus Adaptive. Chapter 2: Agile methodologies, Retrieved 02 October, 2017, from: https://www.applitude.se/2011/02/plan-driven-versus-agile-predictive-versus-adaptive/.
Chung, L. (2012). Non-Functional Requirements. Retrieved 28 September, 2017, from: https://www.utdallas.edu/~chung/SYSM6309/NFR-18-4-on-1.pdf.
Council, C. S. (2017). Impact of Cloud Computing on Healthcare. Version 2.0, Retrieved 02 October, 2017, from: https://www.cloud-council.org/deliverables/CSCC-Impact-of-Cloud-Computing-on-Healthcare.pdf.
Feher, D. (2013). What are the pros and cons of the waterfall and agile/scrum project management approach? . Quora, Retrieved 02 October, 2017, from: https://www.quora.com/What-are-the-pros-and-cons-of-the-waterfall-and-agile-scrum-project-management-approa.
Gupta, N. (2014). Project Management Life Cycle-Iterative & Adaptive. . IZenBridge, Retrieved 02 October, 2017, from: https://www.izenbridge.com/blog/project-management-life-cycle-iterative-adaptive/.
Hassan, A. (2015). Software Architecture. CISC 322, Retrieved 28 September, 2017, from: https://research.cs.queensu.ca/~ahmed/home/teaching/CISC322/F09/slides/CISC322_02_Requirements.pdf.
Kathuria, K. (2011). Software Development Lifecycle and Cloud Computing. . Scribd, Retrieved 02 October, 2017, from: https://www.scribd.com/document/37345932/SDLC-and-Cloud-Computing.
Losavio, F., & Chirinos, L. (2003). Quality Characteristics for Software Architecture. JOURNAL OF OBJECT TECHNOLOGY, Retrieved 02 October, 2017, from: https://www.jot.fm/issues/issue_2003_03/article2.pdf.
Mikoluk, K. (2013). Agile vs. Waterfall: Evaluating The Pros and Cons. Udemy blog, Retrieved 02 October, 2017, from: https://blog.udemy.com/agile-vs-waterfall/.
Utexas. (2017). The System Development Life Cycle. . Retrieved 02 October, 2017, from: https://utexas.instructure.com/courses/1166782/files/38198507.
Velagapudi, M. (2012). SDLC for Cloud Computing – How Is It Different From the Traditional SDLC? . Retrieved 02 October, 2017, from: https://bootstraptoday.wordpress.com/2012/02/06/sdlc-for-cloud-computing-how-is-it-different-from-the-traditional-sdlc/.
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