- the basic interpretation of Action-tokens is already in place
- add the interpretation of conditional and looping constructs
- this includes helpers for
* reset to another Action-token index
* recursive interpretation of the next token
* handling of nested loop evaluation context
In order to make this implementation compile, also the skeleton
of the Map-string-string data binding must be completed, including
a draft how to handle nested keys in a simple map
Sting-view is tricky, since it deliberately does not define a
conversion operator; rather, string has an explicit constructor.
This design was chosen on purpose, since creating a string will
„materialise“ the string-view, which could have severe performance
ramifications when done automatically.
Regarding Lumiera's string-conversion tooling, it seems indicated
thus to add std::string_view explicitly as a known conversion path,
even while this conversion does not happen implicitly.
playing the »fence post problem« the other way round
and abandoning the ''pull processing'' in favour of direct manipulation
leads to much clearer formulation of the code-generation logic
...turns out the ''pipeline design'' is not a good fit for the
Action compilation, since the compiler needs to refer to previous Actions;
better to let the compiler ''build'' the `ActionSeq`
...implemented as »custom processing layer« within a
demand-driven parsing pipeline, with the ability to
inject additional Action-tokens to represent the intermittent
constant text between tags; special handling to expose one
constant postfix after the last active tag.
MatchSeq was imported recently from the Yoshimi-testsuite,
as supporting helper for the CSV table component.
Actually this is just a thin wrapper on top of std::regex_iterator,
which in turn has properties and behaviour very similar to Lumiera's
»Forward Iterator« concept (in fact, it was a source of inspiration to
generalise such a pattern).
So this is an obvious round out and cleanup, as it requires just some
minor additions and adjustments to allow processing a sequence of matches
through a for-loop or some elaborate pipelining setup.
The way I've written this helper template, as a byproduct
it is also possible to maintain the back-refrence to the container
through a smart-ptr. In this case, the iterator-handle also manages
the ownership automatically.
...mostly we want the usual convenient handling pattern for iterators,
but with the proviso actually to perform an access by subscript,
and the ability to re-set to another current index
* establish the feature set to provide
* choose scheme for runtime representation
* break down analysis to individual parsing and execution steps
* conclude which actions to conduct and the necessary data
* derive the abstract binding API required
Conducted an extended investigation regarding text templating
and the library solutions available and still maintained today.
The conclusion is
* there are some mature and widely used solutions available for C++
* all of these are considered a mismatch for the task at hand,
which is to generate Gnuplot scripts for test data visualisation
Points of contention
* all solutions offer a massive feature set, oriented towards web content generation
* all solutions provide their own structured data type or custom property-tree framework
**Decision** 🠲 better to write a minimalistic templating engine from scratch rather
In the Lumiera code base, we use C-String constants as unique error-IDs.
Basically this allows to create new unique error IDs anywhere in the code.
However, definition of such IDs in arbitrary namespaces tends to create
slight confusion and ambiguities, while maintaining the proper use statements
requires some manual work.
Thus I introduce a new **standard scheme**
* Error-IDs for widespread use shall be defined _exclusively_ into `namespace lumiera::error`
* The shorthand-Macro `LERR_()` can now be used to simplify inclusion and referral
* (for local or single-usage errors, a local or even hidden definition is OK)
reduce footprint of lib/util.hpp
(Note: it is not possible to forward-declare std::string here)
define the shorthand "cStr()" in lib/symbol.hpp
reorder relevant includes to ensure std::hash is "hijacked" first
In the Lumiera code base, a convenient string conversion is used
an many places, and is also ''magically'' integrated into the usual
C++ style output with `<<` operators.
However, there is a ''gotcha'' — in the ''rare cases'' when we
actually want to use the C++ input/output framework to copy stream
data from an input source into an output sink, obviously we do not want
the input source to be »string converted«....
showDecimal -> decimal10 (maximal precision to survive round-trip through decimal representation=
showComplete -> max_decimal10 (enough decimal places to capture each possible distinct floating-point value)
Use these new functions to rewrite the format4csv() helper
...this uncovered one inconsistency: when directly adding values
into one of the embedded data vectors, the inconsistent size
was allowed to persist even when adding / removing lines.
This is in contradiction to the behavior for the CSV dump,
which uses index positions from the front of all vectors uniformely.
Thus changed the behaviour of adding a new row, so that it now
caps all vectors to a common size
also added function to clear the table
verify also that clean-up happens in case of exceptions thrown;
as an aside, add Macro to check for ''any'' exception and match
on something in the message (as opposed to just a Lumiera Exception)
...using the same method for sake of uniformity
Also move the permissions helpers to the file.hpp support functions
and setup a separate unit test for these
Inspired by https://stackoverflow.com/a/58454949
Verified behaviour of fs::create_directory
--> it returns true only if it ''indeed could create'' a new directory
--> it returns false if the directory exists already
--> it throws when some other obstacle shows up
As an aside: the Header include/limits.h could be cleaned up,
and it is used solely from C++ code, thus could be typed, namespaced etc.
Since this is a much more complicated topic,
for now I decided to establish two instances through global variables:
* a sequence seeded with a fixed starting value
* another sequence seeded from a true entropy source
What we actually need however is some kind of execution framework
to define points of random-seeding and to capture seed values for
reproducible tests.
Relying on random numbers for verification and measurements is known to be problematic.
At some point we are bound to control the seed values -- and in the actual
application usage we want to record sequence seeding in the event log.
Some initial thoughts regarding this intricate topic.
* a low-ceremony drop-in replacement for rand() is required
* we want the ability to pick-up and control each and every usage eventually
* however, some usages explicitly require true randomness
* the ability to use separate streams of random-number generation is desirable
Yesterday I decided to include some facilities I have written in 2022
for the Yoshimi-Testsuite. The intention is to use these as-is, and just
to adapt them stylistically to the Lumiera code base.
However — at least some basic documentation in the form of
very basic unit-tests can be considered »acceptance criteria«
- reformat in Lumieara-GNU style
- use the Lumiera exceptions
- use Lumiera format-string frontend
- use lib/util
NOTE: I am the original author of the code introduced here,
and thus I can re-license it under GPL 2+
[http://yoshimi.sourceforge.net/ Yoshimi] is a software sound synthesizer,
derived from `ZynAddSubFx` and developed by an OpenSource community.
The Repository [https://github.com/Ichthyostega/yoshimi-test/ Yoshimi-test]
is used by the Yoshimi developers to maintain a suite of automated
acceptance tests for the Yoshimi application.
This task involves watching execution times to detect long-term performance trends,
which in turn requires to maintain time-series data in CSV files and to perfrom some
simple statistic calculations, including linear regression. Requiring any external
statistics package as dependency was not deemed adequate for such a simple task,
and thus a set of self-contained helper functions was created as a byproduct.
This task attaches an excerpt of the Yoshimi-test history with those helpers.
- better use a Test-Chain-Load without any dependencies
- schedule all at once
- employ instrumentation
- use the inner »overall time« as dependent result variable
The timing results now show an almost perfect linear dependency.
Also the inner overall time seems to omit the setup and tear-down time.
But other observed values (notably the avgConcurrency) do not line up
In binary search, in order to establish the invariant initially,
a loop is necessary, since a single step might not be sufficient.
Moreover, the ongoing adjustments jeopardise detection of the
statistical breaking point condition, by causing a negative delta
due to gradually approaching the point of convergence -- leading
to an ongoing search in a region beyond the actual breaking point.
Relying on the new instrumentation facility, the actually effective
concurrency and cumulative run time of the test jobs can be established.
These can now be cast into a form-factor to represent actual excess expenses
in relation to the theoretical model.
By allowing to adjust the adapted schedule by this form factor,
it can be made to reflect more closely the actual empiric load,
hopefully leading to a more realistic effect of the stress-factor
and thus results better suited to conclude on generic behaviour.
- supplement the pre-dimensioning for data capture; without that,
sporadic memory corruption indeed happens (as expected, since
concurrent re-allocation of the vector with an entry for each
thread is not threadsafe, and this test shows much contention)
- add a top-level logging for better diagnostics of errors
emanating from the test run
Basically users are free to place the measurement calls to their liking.
This implies that bracketed measurement intervals can be defined overlapping
even within a single thread, thereby accounting the overlapping time interval
several times. However, for the time spent per thread, only actual thread
activity should be counted, disregarding overlaps. Thus introduce a
new aggregate, ''active time'', which is the sum of all thread times.
As an aside, do not need explicit randomness for the simple two-thread
test case — timings are random anyway...
+ bugfix for out-of-bounds access
...since we've established already an integration over the event timeline,
it is just one simple further step to determine the concurrency level
on each individual segment of the timeline. Based on this attribution
- the averaged concurrenty within the observation range can be computed as weighted mean
- moreover we can account for the precise cumulated time spent at each concurrency level
...using a simplistic allocation of next-slot based on initialisation
of a thread_local storage. This implies that this helper can not be
reset or reused, and that there can not be multiple or long-lived instances.
Keep-it-simple for now...
...to sort out the interpretation of measurement results,
the actual duration and concurrency of ComputationLoad invocations
should be recorded, allowing to draw conclusions regarding the
Scheduler's performance as opposed to further system and thread
management effects due to concurrent operation under pressure.
