lib: optimize internal Web IDL dictionaries

[panva]

Flatten dictionary members at construction while preserving inheritance order. Skip member scans for nullish inputs without defaults or required members, and define own descriptor properties to avoid inherited setters.

[github-actions]

Benchmark GHA (misc / webcrypto-webidl): https://github.com/nodejs/node/actions/runs/34041429199

Results

[!WARNING]
Do not take GHA benchmark results as face value, always confirm them
using a dedicated machine, e.g. Jenkins CI.

Benchmark results:

                                                                           confidence improvement accuracy (*)   (**)   (***)
misc/webcrypto-webidl.js n=1000000 op='normalizeAlgorithm-dict'                            2.94 %       ±4.86% ±6.41%  ±8.23%
misc/webcrypto-webidl.js n=1000000 op='normalizeAlgorithm-string'                          2.91 %       ±4.59% ±6.05%  ±7.77%
misc/webcrypto-webidl.js n=1000000 op='webidl-algorithm-identifier-object'                 0.45 %       ±6.31% ±8.32% ±10.67%
misc/webcrypto-webidl.js n=1000000 op='webidl-algorithm-identifier-string'                 0.68 %       ±5.78% ±7.62%  ±9.77%
misc/webcrypto-webidl.js n=1000000 op='webidl-dict-enforce-range'                          1.40 %       ±5.66% ±7.46%  ±9.57%
misc/webcrypto-webidl.js n=1000000 op='webidl-dict-ensure-sha'                             1.26 %       ±5.27% ±6.95%  ±8.91%
misc/webcrypto-webidl.js n=1000000 op='webidl-dict-null'                          ***     46.44 %       ±5.52% ±7.27%  ±9.34%
misc/webcrypto-webidl.js n=1000000 op='webidl-dict'                                 *      5.36 %       ±5.09% ±6.71%  ±8.61%

Be aware that when doing many comparisons the risk of a false-positive
result increases. In this case, there are 8 comparisons, you can thus
expect the following amount of false-positive results:
  0.40 false positives, when considering a   5% risk acceptance (*, **, ***),
  0.08 false positives, when considering a   1% risk acceptance (**, ***),
  0.01 false positives, when considering a 0.1% risk acceptance (***)

[!WARNING]
Do not take GHA benchmark results as face value, always confirm them
using a dedicated machine, e.g. Jenkins CI.