1 files changed, 12 insertions, 12 deletions
diff --git a/software/chapter.tex b/software/chapter.tex
index 36e2949..b52764b 100644
--- a/software/chapter.tex
+++ b/software/chapter.tex
@@ -1,5 +1,4 @@
 % TODO: add StoddenVictoria2016a (Enhancing reproducibility for computational methods)
-% TODO: http://pubs.acs.org/doi/10.1021/cen-09535-scitech2
 
 \chapter{Software}
 
@@ -146,11 +145,11 @@ parallelization paradigms''
 \section{Good-enough practices}  % ================================================================
 
 In their [...] perspective, ``Good enough practices in scientific computing'', (from which this
-section gets its name) [WILSON ET AL] describe a set of techniques that, in their words, ``every
-researcher can and should consider adopting''.  %
+section gets its name) \textcite{WilsonGreg2017a} describe a set of techniques that, in their
+words, ``every researcher can and should consider adopting''.  %
 In this section, I attempt to very quickly summarize my personal perspective on what makes good
 software development good---with citations to literature that supports each idea.  %
-These practices are not, generally, ``extra work''.  %
+These practices are not, generally, \emph{extra work}.  %
 In fact, many of them save massive amounts of time and effort in the long \emph{and} short run,
 when properly applied.  %
 
@@ -178,7 +177,7 @@ Choose a non-proprietary format if at all possible---remember: you yourself migh
 to the proprietary software in 10 years.  %
 Choose plain text if you can.  %
 Consider conforming to specifications, such as Tidy Data \cite{WickhamHadley2014a}.  %
-If you must, use open binary formats such as HDF5 [CITE].  %
+If you must, use open binary formats such as HDF5 \cite{FolkMike2011a}.  %
 Put as much metadata as you can into the file.  %
 Any piece of metadata that can automatically be added by the computer is essentially free---you
 might as well do it.  %
@@ -221,7 +220,7 @@ unless your project becomes very important.  %
 Distribute test datasets, when appropriate.  %
 Remember, your tests can serve double duty as simple minimal examples.  %
 
-\textbf{Collaborate and share.} \cite{WilsonGreg2017a}  %
+\textbf{Collaborate and share.} \cite{WilsonGreg2017a, BarnesNick2010a}  %
 If you are part of a team, consider sharing software and collaborating to create it.  %
 Try using practices like code review and issue tracking, but don't feel obligated to use them if it
 doesn't make sense for your project.  %
@@ -229,7 +228,7 @@ When working as part of a team, making incremental changes and using version con
 more important.  %
 Earlier we mentioned ``do not reinvent''.  %
 The other side of that coin is ``if you make something, consider sharing it''.  %
-Put your software on an open platform, like GitHub, and mint a DOI.  %
+Put your software on an open platform, like GitHub \cite{GitHub}, and mint a DOI.  %
 Cite your software, and ask other people who are using your software to do the same.  %
 Choose a license early, and choose permissive and commercially compatible unless you 1. know what
 you are doing and 2. plan to enforce.  %
@@ -371,11 +370,11 @@ backwards compatibility. \cite{FITS, WellsDC1981a}  %
 Fits is still popular in the astronomy community.  %
 
 Today, these hierarchical data formats have gathered under the umbrella of the HDF5 format, built
-and maintained by the HDF Group. [CITE]  %
+and maintained by the HDF Group. \cite{FolkMike2011a}  %
 This format has all of the advantages of FITS, CDF, and NetCDF.  %
 It can support arbitrary datatypes and is optimized to quickly process large and complex
 datasets.  %
-In Python, HDF5 is supported primarily through the h5py package. [CITE]  %
+In Python, HDF5 is supported primarily through the h5py package. \cite{h5py}  %
 
 \section{Scientific Python}  % --------------------------------------------------------------------
 
@@ -384,7 +383,8 @@ SciPy is a collection of ``open-source software for mathematics, science, and eg
 SciPy was an absolute essential component of this dissertation and the work it describes.  %
 There are packages under the SciPy umbrella.  %
 NumPy is a very powerful and fast package for working with multidimensional arrays.
-\cite{vanderWaltStefan2011a}  %
+\cite{OliphantTravisE2006a}  %
 The SciPy library contains a vast number of scientific computing tools, including many mathematical
-operations that this work depends on. [CITE]  %
-Matplotlib is a beautiful visualization package for 1, 2, and 3D plotting. [CITE]  %
+operations that this work depends on. \cite{SciPy}  %
+Matplotlib is a beautiful visualization package for 1, 2, and 3D plotting.
+\cite{HunterJohnD2007a}  %