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In computer science, garbage in, garbage out (GIGO) is the concept that flawed, biased or poor quality ("garbage") information or input produces a result or output of similar ("garbage") quality. The adage points to the need to improve data quality in, for example, programming.
GIGO—Garbage In, Garbage Out; GIMP—GNU Image Manipulation Program; GIMPS—Great Internet Mersenne Prime Search; GIS—Geographic Information System; GLUT—OpenGL Utility Toolkit; GML—Geography Markup Language; GNOME—GNU Network Object Model Environment; GNU—GNU's Not Unix; GOMS—Goals, Operators, Methods, and Selection rules; GPASM ...
"In computer science, garbage in, garbage out (GIGO) is the concept that flawed, or nonsense (garbage) input data produces nonsense output. Rubbish in, rubbish out (RIRO) is an alternate wording. " The principle applies to all logical argumentation: soundness implies validity, but validity does not imply soundness.
Names of many computer terms, especially computer applications, often relate to the function they perform, e.g., a compiler is an application that compiles (programming language source code into the computer's machine language). However, there are other terms with less obvious origins, which are of etymological interest.
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Stop-and-copy garbage collection in a Lisp architecture: [1] Memory is divided into working and free memory; new objects are allocated in the former. When it is full (depicted), garbage collection is performed: All data structures still in use are located by pointer tracing and copied into consecutive locations in free memory.
The ACM Computing Research Repository uses a classification scheme that is much coarser than the ACM subject classification, and does not cover all areas of CS, but is intended to better cover active areas of research. In addition, papers in this repository are classified according to the ACM subject classification.
The group 4 project (10 hours, 6 raw marks). Candidates will need to complete an interdisciplinary project with other science students. This is marked against the personal skills criterion. Both components carry a weightage of 30% (SL) or 20% (HL) of the computer science course.