Hermeneutics In Agile Systems Development
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Hermeneutics in Agile Systems Development
Agile is the new world view of systems development. Structured design is being relegated to systems that have a short development time, the way to develop the software is already known (there is no need for design), and the system will not change in any way during the design. Agile methodologies have been developed over time from developers experiencing success by rejecting the ideas of the structured methodology and the waterfall style of project management. The main strengths of Agile methods are: Visibility (through the looking glass) Adaptability (context calculus) Business Value (incrementally increasing the value) Less Risk (changes are made on a Just In Time bases) The biggest problems with the waterfall techniques are: Risky and expensive. Inability to deal with changing requirements. Problems with late integration. Always required extensive rework to make software usable Business advantages of Agile development: Benefits can be realized early. First to market and early and regular releases. Testing is integrated so there is early recognition of any quality issues. Excellent visibility for key stakeholders ensures expectations are managed. Customer satisfaction through project visibility; customers own the project. Incremental releases reduce risks. Change is accepted, even expected. Cost control - the scope and features are variable, not the cost. Developers feel that they are part of the project and enjoy doing the work. In any form of agile development you are using post-modernist methodologies. Agile is post-modern or post structural. Agile and quality-productivity are the most effective post-modernist movements. Older development methodologies used some rather regulated processes of analyzing the information of a system. In fact they were using hermeneutic since hermeneutics is analysis of information. But their methodology put thought fences around this analysis. This book is proposing using all the powers of hermeneutics in developing software. In particular I include the methods developed in post-structuralist hermeneutics. So we study the system to determine what artifacts are present and how they might fit together in a new system. This process is called archeological layering; and renders artifacts that are associated in layers that belong together in the new system. This provides us with the meanings we need for the system. As we have completed this archeological layering in our present cycle we need to redefine the artifacts and their association to each other into what they will become as useful parts of the new system. I call this Formation Data Context. It is a study if the formation of data through the system we are building. It combines the new data to data already analyzed for formation data context. This process requires recognizing how definitions of terms and even the understanding of meanings is important to making a system useful. Thus we base our development of these understandings on pragmatism. This ultimately leads us in developing a system that is useful. This gives the developer a more complete understanding of the meaning of the information about the system from a proper use of hermeneutics. The process of using the more modern methodologies of hermeneutics also provides a more useful way of putting the information back together in the new system developed out of the project. Dr. Jerome Heath, Ph. D p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000} p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px Times; color: #000000; -webkit-text-stroke: #000000; min-height: 14.0px} span.s1 {font-kerning: none}
Context Based Philosophy
Context Based Philosophy - The goal of this methodology is to develop a philosophy that is not based on negatives. When centering our discussion on truth the evaluation of words, issues, ideas are primarily normative. That means once some idea is brought forward it is evaluated first by normative value considerations. Then the problem is that a lot of things cannot be evaluated for their usefulness because they are questioned on value before we know what they are, before we understand the meaning. So we never even understand the meaning. But, also, the normative judgement is actually a cover for personal bias. The approach then, also, us used to hide extreme biases, since to criticize such bias activity also violates the normative issues. This is why we need to base our inquiry on meaning rather than truth.
Object Oriented Mind
Degrees of Freedom Uncertainty This is the degrees of freedom uncertainty rule [which actually allows us freedom]. We can never be sure which individual went this way and which went the other way [that is what entropy and Carnot’s ‘jinks’ on Maxwell’s demons is all about]. This is a statistical population; there are enough members to apply the statistical rule [the rule of large numbers]. That is the same rule [just inverted] as the degrees of freedom uncertainty principle [which says that you cannot specify Newtonian activity on populations that provide excellent statistical results because of the same theory of large numbers. - You can’t have your cake and eat it too [precisely what Carnoy meant]. Also, the difficulties with this rule could be resolved easily; by applying the viewpoint of harmonics. So, under the degrees of freedom uncertainty [when that applies {strongly enough}] you have harmonics. This is the fact that systems under the rule of degrees of freedom uncertainty and that are constrained [in certain natural or “harmonics” ways.] can form “natural” patterns. Harmonics [the name] refers to the patterns since they form in harmonic kine [a set of eigenfunctions]. The pattern does not specify where any part [molecule] is at or how fast it is going. The pattern is an envelope of probability distribution for the randomly distributed contents. This does not allow Maxwell's Demons to sneak some particles into a special place to violate equilibrium rules. Demythologizing Jung Demythologizing and deconstruction is the territory of the post-structuralist. But reconstruction should be the goal of such endeavors. Here the deconstruction of Jung's archetypes is reconstructed into a meaningful, workable, and useful concept of how the mind works. This effort is about the mind and the algorithms that the mind uses to process information. In the brain, pictures are a very important part of the information processing; but computer processing is approaching that state now as well. Here the mind is the program. That mind can use different algorithms in its programming to solve its “problems”. Recognizing these algorithms is our desire for this study. I start with Jung’s Archetype algorithms and proceed to expand that into a more complete recognition of mental algorithms. The process of understanding conversation is to compare the text of a sentence with contextual information we have. The question is: “How do we store and retrieve the context in our grammar?” It is not stored using relational algebra, which is the method we use to store computer database data for efficient computer store and retrieve mechanisms. Relational data storage is not fast enough and it is not broad enough in its combinatorial strength to explain the minds process. The mind has a way of producing mental objects out of the interpretation of external information. A fresh encounter with the outer world is analyzed by a neural network. The information is carried by nerves from the sensing point. These nerve signals are then filtered through neural networks. The archetype [Jung] for that area of mental processing is the link with the conscious. From this link, a memory object can be extended from the archetype (as base class). Then the extended archetype layer becomes the output layer of the neural network. Note the archetype layer serves both as the interpretation function determining layer (how the input is interpreted) and, in the instantiation of the object from the base class extended to a memory object from (based on the neural interpretation). This is a probabilistic process that is under constraints. The process is probabilistic but the constraints provide limitations so the result that is controlled by these limitations produces a meaningful pattern. Thus the constraints prevent dissipation, and encourage meaningful results. The constraints in the young child are the archetypes. As we grow older our minds develop aggregate (abstract) classes that are useful as though they were archetypes. These archetypes and aggregates constrain the mental process so that meaningful patterns result from the interpretation process. The features of the archetypal classes, relating to the attributes and methods of a class, are then the similar to the neural network activation functions. With input (our nerves send these signals about our present context) these features are used to interpret the signals (our internal program adapts them to interpretation of the input signals). When applied to a memory object in our conscious mind, the features (activation functions) are used in a way that they make the memory object useful and meaningful in our thought process. Remember the class here is a (hidden) layer of the neural network not a single node. Also an abstract class can be extended into a memory object (as a real [visible] class). (Also see books by Dr. Jerome Heath: https://sites.google.com/site/jbhcontextcalculus/)