@@ -36,10 +36,10 @@ method ensures the reliability and integrity of scientific knowledge. It
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establishes a framework where hypotheses are not just tested but also subjected
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to repeated verification, underpinning the trust and credibility that society
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places in scientific discoveries. The journey of reproducibility, originating
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- from the earliest scientific endeavors , has evolved to adapt to the complexities
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- and nuances of modern research methodologies. This evolution mirrors the
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- progression of scientific thought and technology, from rudimentary experiments
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- to sophisticated, computer-assisted analyses.
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+ from the earliest scientific endeavours , has evolved to adapt to the
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+ complexities and nuances of modern research methodologies. This evolution
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+ mirrors the progression of scientific thought and technology, from rudimentary
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+ experiments to sophisticated, computer-assisted analyses.
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One can observe the glimpse of the first traces of this concept in @kpopper1934 .
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The concept of reproducibility is far from new and has been a cornerstone in the
@@ -1136,7 +1136,7 @@ meticulously control or normalise the environment in which computations occur.
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By ensuring that ideally environment remains constant, we can more closely
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approximate the behaviour of pure computations in practical software systems.
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This approach does not merely aim to simplify the computational model but serves
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- as a strategic endeavor to minimise the unpredictability introduced by varying
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+ as a strategic endeavour to minimise the unpredictability introduced by varying
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environments.
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In conclusion, while the formalism of computations' purity and reproducibility
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