Minification is a widely-accepted technique which aims at reducing the size
of the code transmitted over the web. We study the problem of minifying
Cascading Style Sheets (CSS) --- the de facto language for styling web
documents. Traditionally, CSS minifiers focus on simple syntactic
transformations (e.g. shortening colour names). In this paper, we propose a new
minification method based on merging similar rules in a CSS file.
We consider safe transformations of CSS files, which preserve the semantics
of the CSS file. The semantics of CSS files are sensitive to the ordering of
rules in the file. To automatically identify a rule merging opportunity that
best minimises file size, we reduce the rule-merging problem to a problem on
CSS-graphs, i.e., node-weighted bipartite graphs with a dependency ordering on
the edges, where weights capture the number of characters (e.g. in a selector
or in a property declaration). Roughly speaking, the corresponding CSS-graph
problem concerns minimising the total weight of a sequence of bicliques
(complete bipartite subgraphs) that covers the CSS-graph and respects the edge
order.
We provide the first full formalisation of CSS3 selectors and reduce
dependency detection to satisfiability of quantifier-free integer linear
arithmetic, for which highly-optimised SMT-solvers are available. To solve the
above NP-hard graph optimisation problem, we show how Max-SAT solvers can be
effectively employed. We have implemented our algorithms using Max-SAT and
SMT-solvers as backends, and tested against approximately 70 real-world
examples (including the top 20 most popular websites). In our benchmarks, our
tool yields larger savings than six well-known minifiers (which do not perform
rule-merging, but support many other optimisations). Our experiments also
suggest that better savings can be achieved in combination with one of these
six minifiers
