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A lightweight methodology is a software development method that has only a few rules and practices, or only ones that are easy to follow. In contrast, a complex method with many rules is considered a "heavyweight methodology". [1] Examples of lightweight methodologies include:
Choosing a research question is an essential element of both quantitative and qualitative research. Investigation will require data collection and analysis, and the methodology for this will vary widely. Good research questions seek to improve knowledge on an important topic, and are usually narrow and specific. [1]
Lightweight programming languages are designed to have small memory footprint, are easy to implement (important when porting a language to different computer systems), and/or have minimalist syntax and features. [1] These programming languages have simple syntax and semantics, so one can learn them quickly and easily.
Multimethodology or multimethod research includes the use of more than one method of data collection or research in a research study or set of related studies.Mixed methods research is more specific in that it includes the mixing of qualitative and quantitative data, methods, methodologies, and/or paradigms in a research study or set of related studies.
Heuer outlines the ACH process in considerable depth in his book, Psychology of Intelligence Analysis. [1] It consists of the following steps: Hypothesis – The first step of the process is to identify all potential hypotheses, preferably using a group of analysts with different perspectives to brainstorm the possibilities.
In computer operating systems, a light-weight process (LWP) is a means of achieving multitasking. In the traditional meaning of the term, as used in Unix System V and Solaris , a LWP runs in user space on top of a single kernel thread and shares its address space and system resources with other LWPs within the same process .
The multiplicative weights update method is an algorithmic technique most commonly used for decision making and prediction, and also widely deployed in game theory and algorithm design. The simplest use case is the problem of prediction from expert advice, in which a decision maker needs to iteratively decide on an expert whose advice to follow.
Morphological analysis or general morphological analysis is a method for exploring possible solutions to a multi-dimensional, non-quantified complex problem. It was developed by Swiss astronomer Fritz Zwicky . [ 1 ]