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Pointers and dynamic memory allocation

2012· book-chapter· en· W74910209 on OpenAlexaff
David Yevick

Bibliographic record

VenueCambridge University Press eBooks · 2012
Typebook-chapter
Languageen
FieldComputer Science
TopicParallel Computing and Optimization Techniques
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPointer (user interface)Computer scienceC dynamic memory allocationVariable (mathematics)Memory safetyBlock (permutation group theory)CompilerOperating systemParallel computingMemory managementComputer hardwareSemiconductor memoryMathematics

Abstract

fetched live from OpenAlex

A pointer variable like a reference or array variable stores a memory address ; however, this address can be arbitrarily changed, enabling the contents of any accessible memory location to be addressed and manipulated directly. While enabling access to all available resources, new and subtle types of errors arise. For example, when a program requests additional memory during runtime from the operating system, the address of the starting location to the new, dynamically allocated variable is returned. Since the value stored in a preexisting compiler-allocated pointer variable can be altered, the running program can preserve the address passed back by the operating system. However, if the pointer variable was defined within an inner block, it will be destroyed when the block terminates. The location of the dynamically allocated memory is then lost and the memory cannot subsequently be accessed or later freed. Introduction to pointers A definition in C++ establishes the amount of memory space required for a variable and the interpretation of the value stored at this memory location. The value of a pointer variable is associated with the starting memory address of a variable of a specified type , i.e. the value of a pointer is a memory address . That is, a double pointer that stores a value such as 80000 interprets the 8-byte region from physical memory location 80000 to location 80007 as the storage location of a double variable. The amount of memory space reserved by any pointer variable equals the number of bits required to store a hardware memory address – on a 32-bit machine, an address requires 4 bytes so that applying the sizeof( ) function to any pointer yields 4 .

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.003
Science and technology studies0.0010.003
Scholarly communication0.0030.006
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.014
GPT teacher head0.200
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2012
Admission routes1
Has abstractyes

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