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Results for Top-down and bottom-up design
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(industrial engineering) A design methodology that proceeds from the highest level to the lowest and from the general to the particular, and that provides a formal mechanism for breaking complex process designs into functional descriptions, reviewing progress, and allowing modifications.
Top-down and bottom-up are strategies of information processing and knowledge ordering, mostly involving software, and by extension other humanistic and scientific system theories (see systemics).
In a top-down approach an overview of the system is first formulated, specifying but not detailing any first-level subsystems. Each subsystem is then refined in yet greater detail, sometimes in many additional subsystem levels, until the entire specification is reduced to base elements. A top-down model is often specified with the assistance of "black boxes" that make it easier to manipulate. However, black boxes may fail to elucidate elementary mechanisms or be detailed enough to realistically validate the model.
In a bottom-up approach the individual base elements of the system are first specified in great detail. These elements are then linked together to form larger subsystems, which then in turn are linked, sometimes in many levels, until a complete top-level system is formed. This strategy often resembles a "seed" model, whereby the beginnings are small, but eventually grow in complexity and completeness. However, "organic strategies", may result in a tangle of elements and subsystems, developed in isolation, and subject to local optimization as opposed to meeting a global purpose.
In the software development process, the top-down and bottom-up approaches play a key role.
Top-down approaches emphasise planning and a complete understanding of the system. It is inherent that no coding can begin until a sufficient level of detail has been reached in the design of at least some part of the system. The Top-Down Approach is done by attaching the stubs in place of the module. This, however, delays testing of the ultimate functional units of a system until significant design is complete. Bottom-up emphasizes coding and early testing, which can begin as soon as the first module has been specified. This approach, however, runs the risk that modules may be coded without having a clear idea of how they link to other parts of the system, and that such linking may not be as easy as first thought. Re-usability of code is one of the main benefits of the bottom-up approach.[citation needed]
Top-down design was promoted in the 1970s by IBM researcher Harlan Mills and Niklaus Wirth. Mills developed structured programming concepts for practical use and tested them in a 1969 project to automate the New York Times morgue index. The engineering and management success of this project led to the spread of the top-down approach through IBM and the rest of the computer industry. Niklaus Wirth, among other achievements the developer of Pascal programming language, wrote the influential paper Program Development by Stepwise Refinement. Top-down methods were favored in software engineering until the rise of object-oriented programming in the late 1980s.
Modern software design approaches usually combine both top-down and bottom-up approaches. Although an understanding of the complete system is usually considered necessary for good design, leading theoretically to a top-down approach, most software projects attempt to make use of existing code to some degree. Pre-existing modules give designs a bottom-up flavour. Some design approaches also use an approach where a partially-functional system is designed and coded to completion, and this system is then expanded to fulfill all the requirements for the project.
Top-down programming is a programming style, the mainstay of traditional procedural languages, in which design begins by specifying complex pieces and then dividing them into successively smaller pieces. Eventually, the components are specific enough to be coded and the program is written. This is the exact opposite of the bottom-up programming approach which is common in object-oriented languages such as C++ or Java.
The technique for writing a program using top-down methods is to write a main procedure that names all the major functions it will need. Later, the programming team looks at the requirements of each of those functions and the process is repeated. These compartmentalized sub-routines eventually will perform actions so simple they can be easily and concisely coded. When all the various sub-routines have been coded the program is done.
By defining how the application comes together at a high level, lower level work can be self-contained. By defining how the lower level objects are expected to integrate into a higher level object, interfaces become clearly defined.
Advantages of top-down programming:
Disadvantages of top-down programming:
Parsing is the process of analyzing an input sequence (such as that read from a file or a keyboard) in order to determine its grammatical structure. This method is used in the analysis of both natural languages and computer languages, as in a compiler.
Bottom-up parsing is a strategy for analyzing unknown data relationships that attempts to identify the most fundamental units first, and then to infer higher-order structures from them. Top-down parsers, on the other hand, hypothesize general parse tree structures and then consider whether the known fundamental structures are compatible with the hypothesis. See Top-down parsing and Bottom-up parsing.
Top-down and bottom-up are used as two approaches for assembling nanoscale materials and devices. Bottom-up approaches seek to have smaller (usually molecular) components arrange themselves into more complex assemblies, while top-down approaches seek to create nanoscale devices by using larger, externally-controlled ones to direct their assembly.
The top-down approach often uses the traditional workshop or microfabrication methods where externally-controlled tools are
used to cut, mill and shape materials into the desired shape and order. Bottom-up approaches, in contrast, use the
Such bottom-up approaches should, broadly speaking, be able to produce devices in parallel and much cheaper than top-down methods, but could potentially be overwhelmed as the size and complexity of the desired assembly increases.
This vocabulary is also employed in neuroscience and psychology. The study of visual attention provides an example. If your attention is drawn to a flower in a field, it may be simply that the flower is more visually salient than the surrounding field. The information which caused you to attend to the flower came to you in a bottom-up fashion -- your attention was not contingent upon knowledge of the flower; the outside stimulus was sufficient on its own. Contrast this situation with one in which you are looking for a flower. You have a representation of what you are looking for. When you see the object you are looking for, it is salient. This is an example of the use of top-down information.
In cognitive terms, two thinking approaches are distinguished. "Top down" (or "big chunk") is stereotypically the visionary, or the person who sees the larger picture and overview. Such people focus on the big picture, and from that derive the details to support it. "Bottom up" (or "small chunk") cognition is akin to focussing on the detail primarily, rather than the landscape. The expression "seeing the wood for the trees" references the two styles of cognition.
In management and organizational arenas, the terms "top down" and "bottom up" are used to indicate how decisions are made.
A "top down" approach is one where an executive, decision maker, or other person or body, makes a decision. this is disseminated under their authority, to lower levels in the hierarchy, who are to a greater or lesser extent, bound by them. For example, a structure in which decisions either are approved by a manager, or approved by his authorised representatives based upon prior guidelines of the manager, is top-down management.
A "bottom up" approach is one which works from the grassroots - from a large number of people working together, causing a decision to arise from their joint involvement. A decision by a number of activists, students, or victims of some incident, to take action, is a "bottom-up" decision.
Often, the École des Beaux-Arts school of design is said to have primarily promoted top-down-design because it taught that an architectural design should begin with a parti, a basic plan drawing of the overall project. By contrast, the Bauhaus focused on bottom-up-design. This method manifested itself in the study of translating small-scale organizational systems to a larger, more architectural scale (as with the woodpanel carving and furniture design).
In ecology, top down control referes to when a top predator controls the structure/population dynamics of the ecosystem. The classic example is of kelp forest ecosystems. In such ecosystems, sea otters are a keystone predator. They prey on urchins which in turn eat kelp. When otters are removed, urchin populations grow and reduce the kelp forest creating urchin barrens. In other words, such ecosystems are not controlled by productivity of the kelp but rather a top predator.
Bottom up control in ecosystems refers to ecosystems in which the nutrient supply and productivity and type of primary producers (plants and phytoplankton) control the ecosystem structure. An example would be how plankton populations are controlled by the availability of nutrients. Plankton populations tend to be higher and more complex in areas where upwelling brings nutrients to the surface.
There are many different examples of these concepts. It is not uncommon for populations to be influenced by both types of control.
J. A. Estes, M. T. Tinker, T. M. Williams, D. F. Doak "Killer Whale Predation on Sea Otters Linking Oceanic and Nearshore Ecosystems", Science 16 October 1998: Vol. 282. no. 5388, pp. 473 - 476
Malone, T. C., D. J. Conley, T. R. Fisher, P. M. Glibert, L.W. Harding & K.G. Sellner, 1996. Scales of nutrient-limited phytoplankton productivity in Chesapeake Bay. Estuaries 19: 371–385.
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