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Diffstat (limited to 'thesis/parts/results.tex')
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diff --git a/thesis/parts/results.tex b/thesis/parts/results.tex index 747631d..dbc8b14 100644 --- a/thesis/parts/results.tex +++ b/thesis/parts/results.tex @@ -41,7 +41,7 @@ It's unsurprising that these two implementations are the cheapest, as they have This is likely due to hash collisions being more likely as the size of the collection increases. \code{BTreeSet} insertions are also expensive, however the cost appears to level out as the collection size goes up (a logarithmic curve). -It's important to note that Rust's \code{BTreeSet}s are not based on binary tree search, but instead a more general tree search originally proposed by R Bayer and E McCreight\parencite{bayer_organization_1970}, where each node contains $B-1$ to $2B-1$ elements in an array. +It's important to note that Rust's \code{BTreeSet}s are not based on binary tree search, but instead a more general tree search originally proposed by R Bayer and E McCreight\citep{bayer_organization_1970}, where each node contains $B-1$ to $2B-1$ elements in an array. Our two mapping types, \code{BTreeMap} and \code{HashMap}, mimic the behaviour of their set counterparts. @@ -92,7 +92,7 @@ This is possibly a case of overfitting, as the observations for both implementat \code{HashSet} appears roughly linear as expected, with only a slow logarithmic rise, probably due to an increasing amount of collisions. \code{BTreeSet} is consistently above it, with a slightly higher logarithmic rise. -The standard library documentation states that searches are expected to take $B\log(n)$ comparisons on average\parencite{rust_documentation_team_btreemap_2024}, which is in line with observations. +The standard library documentation states that searches are expected to take $B\log(n)$ comparisons on average\citep{rust_documentation_team_btreemap_2024}, which is in line with observations. \code{BTreeMap} and \code{HashMap} both mimic their set counterparts, though are more expensive in most places. This is probably due to the increased size more quickly exhausting CPU cache. @@ -120,7 +120,7 @@ Future improvements could address the overfitting problems some operations had, Our test cases broadly fall into two categories: Example cases, which just repeat a few operations many times, and our 'real' cases, which are implementations of common algorithms and solutions to programming puzles. We expect the results from our example cases to be relatively unsurprising, while our real cases are more complex and harder to predict. -Most of our real cases are solutions to puzzles from Advent of Code\parencite{wastl_advent_2015}, a popular collection of programming puzzles. +Most of our real cases are solutions to puzzles from Advent of Code\citep{wastl_advent_2015}, a popular collection of programming puzzles. Table \ref{table:test_cases} lists and briefly describes our test cases. \begin{table}[h!] |