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Sometimes, standard semantical approaches assume a target stack-machine, or SSA architecture, or something else with insufficient generality to cover all the cases we want (e.g., non-Von architectures like APU from GSIT). ASR assumes only lambda/pi/rho calculus, depending on whether you want concurrency semantics (that's TBD, frankly; today it's justs lambda)
Some IDEs have incremental compilers that are sufficiently fast to update squigglies and what-not on every keystroke. Compilation speed is a primary value, in general.
Right. Decompilation with ASR should be relatively easy and more faithful than average decompilation (though, as mentioned by another commenter, the very-long-term value of decompilation in general is debatable in the face of rising AI like CoPilot).
Implication is that ASR is a full programming language in its own right (though with no quality-of-life features: everything is explicit, and it's also currently restricted to the operations featured by LFortran and LPython: heavily array-oriented for now, ASR grows as LFortran and LPython grow). I've prototyped, in Clojure, an independent type-checker for ASR (https://github.com/rebcabin/masr), and an interpreter (for "abstract execution") should not be difficult.
A particular advantage of subsetting the language is that LPython inherits all the tooling of Python. I use pudb and PyCharm daily to develop LPython code.
ASR abstracts away all syntax and all details of the target machine, no leaks. Contrast to the schoolbook approach of decorating ASTs with semantic information, which often reflects details of a target machine.