Defined System Development Methodologies

In terms of scrum methodology, system development refers to the way in which logical constructs can be executed in the form of computer data. The structure is made up of several key components, such as inputs, processes, and both marco and micro outputs. Marco outputs refer to the whole project as a whole, like micro outputs are related to relative steps within the whole construct. The combination of all of these elements creates an implemented system.

Within the system we also find smaller constructs, such as artifacts. These consist of documents, models, programs, test cases and other observable objects created before the implemented system. Usually their initial purpose is to simplify the process, and to support thinking, check completeness and create audit trials. In the process of system development, these also have to be turned into logical data. Usually this occurs through the use of a metamodel, which defines the semantic, or written content of model artifacts. To aid the construction of visual explanations, notation is used to describe the graphing and documentation conventions that the models are made up of.

System development method

The way in which a system is developed is commonly known as a method. A method is essentially a framework, which defines the logical process for constructing systems, and the way in which these systems are implemented. It can also be referred to as a metaprocess, i.e. a process for modeling processes. It consists of defining, building and implementing a system. For a system to be classified as a theoretical system, it must be derived from first principles, using substantial material and underlying laws that determine the model. Only if it conforms to these constructs can it be considered a theoretical process.

Theoretical model

There are several upsides to theoretical modeling over empirical modeling, which relies on observed inputs and outputs without depending on any laws during the construction process and strictly depending on experimentally obtained information. The key benefit is time. Because theoretical modeling is based on a template, it only involves the estimation of the unknown parameters in a model, as opposed to the model as a whole. This means that fewer measurements are necessary for the model to operate effectively.

The subjectivity of the theoretical model provides information about the internal state of the process, including the fundamental understanding of the internal workings of the process. This also refers to another key factor of the model, which requires fairly accurate and complete process knowledge. Because the model itself relies on defined laws and principles, it is necessary to be familiar with what these factors affect and influence once the unknown model parameters are inserted into the construct.

Taking into account that the model itself is fixed and first principles remain constant throughout, the defined system methodology is not useful for poorly understood or complex processes, as it is limited in what it can do given the lack of availability for data construction in the system. Although it is automated, and can produce both linear and nonlinear process models naturally, the system works best with simple, common workflows.

Although defined system methodologies are useful, it is impossible to rely purely on a logical construct to deliver results and solutions. Methods contribute raw logical infrastructure, and can identify where creativity and innovative thinking is needed, but computers are not capable of inventive and original ideas, and this is why in the end, and although the defined system methodology is useful, it is impossible to rely on it throughout the whole process.