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What are good choices to produce charts in computer science research papers? For example, I think Figure 8 from Staring into the Abyss: An Evaluation of Concurrency Control with One Thousand Cores (pdf), included below, is great. What tools were used to produce it?
Source: Xiangyao Yu et al., ibid., p. 215.
You can use TIKZ and PGFPLOTS packages in latex to produce beautiful figures, see these pages for some examples, TIKZ examples and PGFPLOTS examples.
Matlab and python are powerful software for producing nice plots. Barchart creation using Matlab, Barchart Matlab examples, and Python example, Python matplot example.
exportfig. Default setup and default export produce awful grapics, but it is not that difficult to make them look nice. You have to know what you want to do.
– Crowley
Sep 15 '16 at 10:04
To add to other answers that will probably suggest some nice, specific software:
Use whatever you are comfortable with. I personally don't think this figure 8 is that special, and I don't even think it has any features that cannot easily be done with something as common as Excel. As also mentioned in some comments: even the potential graphical powerhouse Matlab will produce crappy figures if you use the standard settings. The same for some other "go-to" software packages. But you have to be able to use them.
In almost all of the mentioned software you can adapt (almost) everything, and some default settings look better than others (one of the reasons why Excel has such a bad reputation).
The most important thing is that you decide how a graph should look, and actually make it look like that. Don't settle for default colors / font sizes and line widths! Whatever software you use to get there is your choice.
If you're fluent in MS Office: probably you should just use Excel. If you like to write scripts and use commands instead of clicking everywhere: Matlab might be an option. If spent 3 years getting good at using Graphpad but don't like how the graphs look? Just adapt them to fit your tastes, don't be limited by the default settings.
And when exporting them use the right settings. Many journals accept vector graphics, which will always look better, but the journal has to accept those. Figures also need to be the right size. Everything can look perfect printed 12 cm wide, but when your graph has to fit one column (8.5 cm), the same graph will look too small with unreadable fonts.
Adding to the other answers for the sake of completeness:
Gnuplot is always an option if you do not want to use Python or R. It is freely available and can be used on most platforms. Also plotting can be automated using shell scripts.
Inkscape is a vectorgraphics tool that can be used to create nice graphics. While it provides a rudimentary function plotter and can render TeX code I would advise against using it to create graphics.
In enhancing plots however, Inkscape can be invaluable. You can use Inkscape to edit svg and pdf files created by other plotting tools, like matplotlib, gnuplot, etc. I use this for grouping, recoloring, editing and adding labels, and other fine tuning tasks.
Inkscape is also available on most platforms. To edit a pdf file just open it with Inkscape (File -> Open).
As others have mentioned, it is not the tool, it is what you do with it. While this might not be a direct answer to the question, I would like to recommend the Edward Tufte's book Envisioning Information. It explores several facets of what makes a good visualization of data and how to highlight what you actually want to show.
Currently, the ggplot package in R is the best for producing very clean plots. matplotlib is fine, but it's not as easy or as flexible as ggplot. seaborn is another python package that wraps around matplotlib to make it a little easier.
But ultimately, as @VonBeche says, do what's most comfortable for you.
@Habi mentioned it already, but I thought I would go into more detail about why PGFPlots.
Here is what might happen over the course of a particular piece of work.
Then stuff happens.
Vs if I was exporting a Plot (and a png, of even svg or pdf, rather than CSV data) from a plotting tool (like matplotlib). I would have to mess around trying to get the size, resolution and color right for all the different versions of the plot -- I find that is much easier to do in latex. And I would need to manage all those different plot files. It is still automatable, but now my presentation settings (style), live with my Analysis (in Jupyter), rather than in with my writeup (in LaTeX).
Side bonus is that Plots produced with PGFPlots use the same font as the rest of your document, and can use named colours you have defined in your document. And the text ends up highlightable (rather than as a image of text).
VonBeche's advice "Use whatever you are comfortable with" is best, no shame in using excel if it works.
That said, may I suggest Plots.jl? It has one of the simplest, but most flexible apis I've seen. The biggest advantage over others is it tries to display something for whatever data you throw at it. It can be as simple as:
plot(rand(10,5))
More complex examples such as animated gifs: 
can be easily built with only a few more lines of code
Best of all, it is a front-end to many of the packages mentioned here (PGFplots, TIKZ, Matplotlib, others such as Plotly), so you can always change your final output format later
It is available as a package for the Julia language - which is a similar system to matlab
