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However, dependencies among statements or instructions may hinder parallelism — parallel execution of multiple instructions, either by a parallelizing compiler or by a processor exploiting [[instruction-level parallelism]]. Recklessly executing multiple instructions without considering related dependences may cause danger of getting wrong results, namely [[Hazard (computer architecture)|hazards]].
==Data Dependency Management==
In 2016, Edgard Marx, a computer scientist from Leipzig University, coined the term Data Dependency Management<ref>{{Cite web|title=Data Dependency Management|url=https://github.com/AKSW/KBox|access-date=2023-07-13|website=github.com|url-status=live}}</ref> to refer to the systems that deal with the management of data.
Data Dependency Management systems are designed to facilitate the deployment and management of data on the cloud, personal computers, or smart devices (edge). Data Dependency Management frameworks can be used to describe how the data was conceived, licensing as well as its dependencies. The concept of data dependency management comes from software package dependency management tools such as npm for JavaScript, [[RubyGems|gem]] for Ruby, and [[NuGet]] for .NET. Their rationale is to allow users to manage the software dependency on data, such as machine learning models for data-driven applications. They are useful to publish, locate, and install data packages. A typical example of a data dependency management frameworks are Hugging Face, KBox,<ref>{{Cite journal|title=KBox|url=https://ieeexplore.ieee.org/document/7889519|access-date=2023-07-13|website=gieeexplore.ieee.org|date=January 2017 |pages=125–132 |doi=10.1109/ICSC.2017.77 |s2cid=14980310 |url-status=live}}</ref> among others.
==References==
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