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Although it is rarely clearly stated, we implicitly have a predicate whose result tells us when an abstract value permits strictness optimisations.
Using partial projections we will introduce strictness behaviour, and propagate it through the program by the projection analysis.
In particular, strictness annotations that may accompany the declaration of a data constructor are not apparent in the concrete syntax of a constructor application.
We provide an abstract semantics based on partial projections which defines a strictness analysis.
Below we present results obtained by the strictness analysis defined above.
In previous formulations of projection strictness analysis, the two forms of demand were confused (literally) by the lifting trick.
The strictness premise is necessary because # is strict in its first argument.
This is contrary to most strictness analysers, where the strictness property of an expression has to be computed anew whenever one of its subexpressions changes.
The strictness annotations on the arguments in these functions can also be derived by a strictness analyser.
Again, the presence of lifting in strictness analysis meant that the two analyses were hard to compare formally.
Corollaries 3.33 and 3.34 claim that strictness information is correctly detected on a custom-tailored input.
A non-compositional approach will need to export the code of the function in order to perform strictness analysis in places where the function is used.
Generally, it is very complicated or even not possible at all to derive such strictness by some kind of static analysis.
In subsection 2.1 we use the notion of contextual equivalence to define strictness of functions.
Given that the intended readership was primarily non-specialist, strictness of terminology may not have been a crucial concern.
