Implemented a function in esbmc_util that uses regex patterns to remove some output
lines to reduce token consmuption and to facilitate the reduction of the likelihood that
LLMs like GPT 3.5 turbo reach the token limit for some codebases that need
comprehensive explanations.

Addded in config.json four new cases that address common bugs in C programs: buffer overflow,
arithmetic overflow, array out-of-bounds and memory leaks.

Signed-off-by: mihai.state <mihaita.state@yahoo.com>

Created more regex patterns that remove some lines that can be ommitted
and provide shorter outputs.
Added a few more indications in the config.json file that
tell the LLM to avoid mentioning time measurements

Signed-off-by: mihai.state <mihaita.state@yahoo.com>

Created new output scenarious in the config.json file
for NaN check, struct fields check, deadlock check and data races check
Created the reduce_output field in the config.json file to tell the
LLM to produce a smaller output
Created new regex patterns in the reduce_output2() function
Created the remove_patterns_nltk that uses NLP methods to identify
patterns in a sequence of tokenized words. The advantage of it are
that it provides more granular control over text sentences, it can
be more precise in some situations.
Created the test_output_reducer file that tests the functionality of the esbmc_output_optimisation(),
reduce_output2() and remove_patterns_nltk() functions that covers all the string patterns
Instantiated the GPT_4_TURBO_PREVIEW model in the enum of the ai_models.py and used it for various
code bases.

Signed-off-by: mihai.state <mihaita.state@yahoo.com>

Removed the 'flags=re.MULTILINE' argument for the regex patterns that work properly without it
Used the re.compile method for some patterns to reduce time complexity

Signed-off-by: mihai.state <mihaita.state@yahoo.com>