Hillel Wayne's post dissects the concept of "nondeterminism" in computer science, arguing that it's often used ambiguously and encompasses five distinct meanings. These are: 1) Implementation-defined behavior, where the language standard allows for varied outcomes. 2) Unspecified behavior, similar to implementation-defined but offering even less predictability. 3) Error/undefined behavior, where anything could happen, often leading to crashes. 4) Heisenbugs, which are bugs whose behavior changes under observation (e.g., debugging). 5) True nondeterminism, exemplified by hardware randomness or concurrency races. The post emphasizes that these are fundamentally different concepts with distinct implications for programmers, and understanding these nuances is crucial for writing robust and predictable software.
Hillel Wayne's blog post, "Five Kinds of Nondeterminism," delves into the nuanced meanings of "nondeterminism" across different computational contexts, meticulously dissecting the term beyond its common association with randomness. Wayne argues that using the term vaguely can lead to confusion and miscommunication, especially in discussions about security and formal methods. He proposes a typology of five distinct categories of nondeterminism, providing clarity and precision to the concept.
The first type is implementation-defined nondeterminism. This arises from specifications leaving certain aspects of a system's behavior deliberately unspecified, allowing for variation across different implementations. While the behavior isn't random for a specific implementation, it is unpredictable a priori without knowing the implementation details. Examples include the order of elements returned from a hash table or the specific optimizations a compiler chooses.
Next, don't care nondeterminism emerges when a specification explicitly allows multiple valid outcomes for a given input, without preference for any specific outcome. The system can choose any of the allowed outcomes, and this choice does not affect the correctness of the system. This is often used in hardware design where certain signal transitions are irrelevant.
Third, demonic nondeterminism pertains to situations where an adversary or malicious actor can influence the behavior of the system within the constraints of its specification. Formal methods, such as model checking, often utilize this type of nondeterminism to analyze worst-case scenarios and guarantee robustness against adversarial manipulation. A critical example involves assessing the security of a system against various attack vectors.
The fourth category, probabilistic nondeterminism, is the type most commonly associated with the term "nondeterminism" in everyday usage. Here, system behavior is governed by probabilities, with different outcomes having specific likelihoods. Random number generators and stochastic processes are prime examples of this type. While individual outcomes are unpredictable, the overall distribution of outcomes is often known or can be statistically characterized.
Finally, scheduler nondeterminism relates specifically to the order of execution in concurrent systems. Multiple processes or threads compete for resources, and the scheduler determines which process gets to execute at a given time. The precise interleaving of execution steps can influence the overall outcome, leading to nondeterministic behavior. This type of nondeterminism poses significant challenges for designing and debugging concurrent systems, necessitating careful synchronization mechanisms to avoid race conditions and other concurrency bugs.
In conclusion, Wayne emphasizes that understanding these different facets of nondeterminism is essential for clear communication and accurate reasoning about complex systems. He provides concrete examples for each type, illustrating their distinct properties and implications. By disambiguating the term "nondeterminism," Wayne equips readers with a more sophisticated and nuanced understanding of the concept and its various manifestations in different computational domains.
Summary of Comments ( 17 )
https://news.ycombinator.com/item?id=43107317
Hacker News users discussed various aspects of nondeterminism in the context of Hillel Wayne's article. Several commenters highlighted the distinction between predictable and unpredictable nondeterminism, with some arguing the author's categorization conflated the two. The importance of distinguishing between sources of nondeterminism, such as hardware, OS scheduling, and program logic, was emphasized. One commenter pointed out the difficulty in achieving true determinism even with seemingly simple programs due to factors like garbage collection and just-in-time compilation. The practical challenges of debugging nondeterministic systems were also mentioned, along with the value of tools that can help reproduce and analyze nondeterministic behavior. A few comments delved into specific types of nondeterminism, like data races and the nuances of concurrency, while others questioned the usefulness of the proposed categorization in practice.
The Hacker News post titled "Five Kinds of Nondeterminism" linking to an article on buttondown.com has generated several comments discussing various aspects of nondeterminism in computer systems.
Several commenters discuss the nuances and overlaps between the different categories of non-determinism outlined in the article. One commenter points out the difficulty in cleanly separating these categories in practice, arguing that many real-world systems exhibit characteristics of multiple types simultaneously. They use the example of a distributed database, which can have both implementation-defined (order of messages) and essential (concurrent user actions) non-determinism.
Another commenter focuses on the performance implications of non-determinism, specifically in the context of compiler optimizations. They suggest that eliminating certain kinds of non-determinism can allow for more aggressive optimizations and improved performance predictability.
The concept of "Heisenbugs" is brought up, with one commenter explaining how these elusive bugs are often a direct consequence of unintended non-determinism. They further link this to the increasing complexity of modern systems and the difficulty in controlling all sources of non-deterministic behavior.
One commenter delves into the philosophical implications of non-determinism, touching upon the free will vs. determinism debate. They propose that the classification of non-determinism in the article could be applied to this philosophical discussion, offering a new perspective on the nature of choice.
There's also a discussion about the role of testing and debugging in the presence of non-determinism. One commenter advocates for designing systems that minimize essential non-determinism, arguing that it simplifies testing and makes debugging easier. Another suggests techniques for reproducing and isolating non-deterministic bugs, emphasizing the importance of logging and careful analysis of system behavior.
A few commenters offer specific examples of non-determinism in different programming languages and systems, illustrating the practical relevance of the article's categorization. They mention issues related to thread scheduling, memory allocation, and network communication, providing concrete examples of how non-determinism manifests in real-world scenarios.
Finally, some commenters express appreciation for the article's clear explanation of a complex topic, finding the categorization helpful for understanding and addressing non-determinism in their own work. They also suggest potential extensions to the article, such as exploring the relationship between non-determinism and formal verification methods.