From b4f42220e029dbc696cfdfbdd93d24aa56678c3b Mon Sep 17 00:00:00 2001 From: "Jip J. Dekker" Date: Sat, 24 Jul 2021 13:50:08 +1000 Subject: [PATCH] Grammar check of the Abstract --- chapters/0_abstract.tex | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/chapters/0_abstract.tex b/chapters/0_abstract.tex index 95b5943..a273892 100644 --- a/chapters/0_abstract.tex +++ b/chapters/0_abstract.tex @@ -12,7 +12,7 @@ However, \cmls{} have evolved to include functionality that is no longer directl As such, the \gls{rewriting} process has become more important and complex. \minizinc{}, one such language, was originally designed for constraint programming \solvers{}, whose \glspl{slv-mod} contain small number of highly complex \constraints{}. -The same \minizinc{} models can now target mixed integer programming and Boolean satisfiability \solvers{}, resulting is a large number of very simple \constraints{}. +The same \minizinc{} models can now target mixed integer programming and Boolean satisfiability \solvers{}, resulting in numerous very simple \constraints{}. Distinctively, the \minizinc{}'s \gls{rewriting} process is founded on its functional language. It generates \glspl{slv-mod} through the application of increasingly complex \minizinc{} functions from \solver{}-specific libraries. Consequently, the efficiency of the functional evaluation of the language can be a limiting factor. @@ -29,6 +29,6 @@ In addition, we incorporate new analysis techniques to avoid the use of \glspl{r Crucially, the architecture is designed to incorporate incremental \constraint{} modelling in two ways. Primarily, the \gls{rewriting} process is fully incremental: changes made to the \instance{} through a provided interface require minimal addition \gls{rewriting} effort. Moreover, we introduce \gls{rbmo}, a way to specify \gls{meta-optimization} algorithms directly in \minizinc{}. -These specification are executed by a normal \minizinc{} \solver{}, requiring only a slight extension of its capabilities. +These specifications are executed by a normal \minizinc{} \solver{}, requiring only a slight extension of its capabilities. Together, the functionality of this architecture helps make \cmls{} a more powerful and attractive approach to solve real world problems.