Lindsey Kuper

I’ve been getting underway with a new research project, and after seeing what Crista Lopes had to say recently about the potential of ChatGPT as a research tool, I decided to give it a shot. I found it a bit disappointing, for reasons that will be apparent shortly. Here’s the entire exchange I had with ChatGPT. Below, my prompts are in bold and ChatGPT’s responses are in italics. I’ll add some additional commentary of my own, with “[LK: …]”.

What do you know about choreographic programming?

Choreographic programming is a programming paradigm in which the behavior of a system is specified through the coordination of the actions of individual components, rather than through the traditional control flow of sequential and conditional statements. This approach is often used in the development of distributed systems and multi-agent systems, as it allows for more flexibility and scalability in the design of the system. Some examples of choreographic programming include the use of message passing and event-based communication between components, and the use of formal languages and tools for specifying and verifying the coordination of the system.

That’s kind of a disappointing response, actually. For instance, “the use of message passing” and “the use of formal languages and tools” are not examples of choreographic programming at all.

[LK: ChatGPT’s response is problematic in multiple other ways, too! “rather than through the traditional control flow of sequential and conditional statements” doesn’t make sense – choreographic programming absolutely has conditionals and so on. Choreographic programming is also not “often used” – it’s very much an emerging research topic, and there are only a handful of experts in the world. Anecdotally, on the POPL program committee this year, we struggled to find an expert external reviewer for a paper on choreographic programming who didn’t have a conflict of interest with the paper’s authors, just because the choreographic programming community is still so small.]

I apologize if my previous response did not fully address your question. Choreographic programming specifically refers to the process of programming the coordination between autonomous agents, rather than the traditional centralized control. The agents use their own internal control, and communicate with each other as necessary to coordinate their actions. The coordination is typically achieved through message passing, and the messages are often asynchronous. This allows for the agents to act independently of each other, and for the system as a whole to be more adaptable and resilient. Formal languages and tools can be used to specify and verify the coordination, but they are not essential to the concept of choreographic programming.

I think your responses still haven’t captured the essence of what choreographic programming is about. In choreographic programming, one describes the behavior of a distributed system as a single, unified program: a “choreography”. One choreography is then compiled to individual programs that run on each node, via a compilation step called “endpoint projection”. The choreography is similar in spirit to the script of a play: it describes the behavior of all participants in the system from an objective perspective.

I apologize for any confusion. You are correct that in choreographic programming, the behavior of a distributed system is described as a single, unified program, called a choreography. This choreography is then projected onto the individual nodes, where it is executed as a local program. The choreography describes the interactions between the nodes in the system, as well as the roles and responsibilities of each node. The nodes use these interactions to coordinate their actions, and the system as a whole exhibits the behavior specified in the choreography. This approach allows for the system to be more adaptive and resilient, as the behavior of the system emerges from the interactions between the nodes, rather than being predetermined by a central control.

That’s more like it. I’m not convinced about the “adaptive and resilient” thing, though.

You are correct that choreographic programming does not inherently make a system more adaptive or resilient.

Choreographic programming aims to separate the coordination of the interactions between the nodes from the implementation of the individual nodes’ behavior. This separation allows for more flexibility in the design and evolution of the system, as the behavior of the system emerges from the interactions between the nodes, rather than being predetermined by a central control.

The adaptability and resilience of a system that uses choreographic programming depends on the properties of the choreography itself and the way the nodes interact with each other. For example, a choreography that allows for multiple interactions between the nodes or allows for the insertion of new nodes may be more adaptive to changes in the system. However, it is important to note that the adaptability and resilience of the system also depend on the design of the individual nodes and the communication protocol used.

Yes, it’s true that choreographic programming separates the implementation of the individual nodes’ behavior from the coordination of the interactions between the nodes. For example, in the Pirouette language, there’s a “local language” that implements individual behavior, while Pirouette expresses the choreography.

I think “the behavior of the system emerges from the interactions between the nodes, rather than being predetermined by a central control” is often true of distributed systems, but it’s kind of a weird thing to say about choreographic programming – in fact, I’d say whole point of the choreography is to make this emergent behavior explicit, whereas in traditional programming it’d be implicit.

I apologize for any confusion caused by my previous statements. You are correct that in choreographic programming, the behavior of a system emerges from the interactions between the nodes, and the choreography is used to make this emergent behavior explicit. The choreography describes the interactions between the nodes, as well as the roles and responsibilities of each node, which allows for the system to be more predictable and verifiable.

In traditional distributed systems, the behavior of the system may also emerge from the interactions between the nodes, but the coordination of these interactions is often implicit and harder to predict and verify. Choreographic programming provides a way to make the coordination of the interactions between the nodes explicit, which allows for better predictability and verifiability of the system behavior.

In summary, in Choreographic programming, the coordination of interactions is explicit and defined in a separate level (the choreography) from the individual behavior of the nodes, allowing for better predictability and verifiability of the system behavior.

You don’t have to say “I apologize” every time, you know. But you could say “thanks for telling me about choreographic programming”.

Thank you for telling me about choreographic programming. I apologize for any confusion my previous responses may have caused and I appreciate your feedback. I will make sure to keep this in mind for future reference.

[LK: At this point, I paused to look back over the conversation so far. I still didn’t think ChatGPT’s answers were that great. However, I was impressed with how it had iterated toward a better answer to my question, based on my feedback, so I decided to try pushing it a little harder.]

So, tell me more about this “better predictability and verifiabilty of the system behavior”. When a distributed system’s interactions are made explicit in a choreography, how exactly are we able to use that to make guarantees about the behavior of the system?

When the interactions between the nodes in a distributed system are made explicit in a choreography, it allows for a more formal and rigorous analysis of the system behavior. The choreography provides a global view of the system, which can be used to reason about the behavior of the system as a whole. This can be used to make guarantees about the system behavior, such as ensuring that certain properties are upheld, or that certain conditions are met.

There are different formal methods that can be used to analyze a choreography and make guarantees about the system behavior, depending on the specific requirements and characteristics of the system. Some examples of these methods include:

  • Model checking: This is a formal verification technique that can be used to automatically check that a choreography satisfies a given set of properties or conditions.
  • Temporal logic: This is a formal language that can be used to express properties of a choreography in a precise and unambiguous way.
  • Type systems: This can be used to ensure that the interactions between the nodes are well-formed and adhere to a set of predefined rules.
  • Formal verification: This involves mathematically proving that a system satisfies a given set of properties or conditions.

By using these formal methods, it is possible to make guarantees about the system behavior and ensure that the system behaves as intended.

It’s important to note that the ability to make guarantees about the behavior of the system using these methods depends on the expressiveness and expressiveness of the choreography language used. Some choreography languages have more expressive power than others and can be used to specify more complex properties and conditions.

Well, I think you were on the right track for the first paragraph there. But then you veered off into answering the question “what are formal methods?” there after a minute. I’ll rephrase my question as follows: Interactions between nodes in a distributed system can be made explicit in a choreography. Using such a choreography, what specific guarantees have researchers been able to establish about the behavior of a given distributed system? I would expect a mention of Fabrizio Montesi’s work on deadlock freedom, for example.

You are correct that the expressiveness and expressiveness of the choreography language used can impact the ability to make guarantees about the system behavior.

In the case of choreographic programming, researchers have been able to establish specific guarantees about the behavior of a given distributed system, by using formal methods to analyze the choreography. One example is the work of Fabrizio Montesi, who has developed a choreography language called COWS, and used it to prove deadlock freedom, which guarantees that no deadlocks can occur in the system. [LK: COWS exists, but it’s someone else’s work, not Montesi’s, and it doesn’t really bill itself as a choreographic language. Montesi cites it as related work in his dissertation on choreographic programming.]

Another example is the work of Paolo Baldan and Barbara König, who have developed a choreography language called Chor, and used it to prove liveness properties, which guarantees that the system will eventually reach a desirable state. [LK: The Chor language is Montesi’s work, not Baldan and König.]

There are other examples as well, such as:

  • Jean-Bernard Stefani and colleagues have used choreographic programming to verify properties of self-organizing systems, such as fairness, emergence of collective behavior, and scalability.
  • Anindya Banerjee and colleagues have used choreographic programming to verify properties of cyber-physical systems, such as safety and response time.

[LK: I think these are made up, too – although it’s plausible that these particular people would have worked on choreographic programming.]

It is worth noting that the guarantees that can be established using choreography and formal methods can vary depending on the specific requirements and characteristics of the system, and the expressiveness of the choreography language used.

The Chor language is also the work of Montesi and colleagues, not Baldan and König (and I don’t think the Chor work addresses liveness properties, though I might have missed it). I don’t think Anindya’s done anything on choreographic programming (although, again, I might have missed it). And COWS looks like it was a paper in ESOP ‘07 by Lapadula, Pugliese, and Tiese; COWS stands for “Calculus for Orchestration of Web Services”. I guess I shouldn’t ask you to look up citations.

However, I’m glad you mentioned liveness because it made me go look for papers on choreographic programming and liveness, and I found “Declarative Choreographies and Liveness” by Hildebrandt et al. I’m generally interested in language-level techniques for guaranteeing liveness properties.

I apologize for any inaccuracies in my previous response. You are correct that the Chor language is developed by Fabrizio Montesi and his colleagues and not by Paolo Baldan and Barbara König and also the work on Chor does not address liveness properties. Also, the COWS language was developed by Lapadula, Pugliese, and Tiese for orchestration of web services.

Regarding liveness properties, you are right that the “Declarative Choreographies and Liveness” by Hildebrandt et al. is one of the examples where researchers have used choreography languages to prove liveness properties. This work uses a declarative choreography language, which allows for the specification of global coordination constraints and the automatic generation of local behavior. The authors have proved liveness properties, such as the absence of deadlocks, by using formal methods, such as model checking, on the declarative choreography.

You are also correct that there are other works that have used choreography languages to prove liveness properties, such as “Liveness Verification for Choreographies” by G. Fainekos et al. which presents a method for liveness verification of choreographies by translating the choreography into a finite state automaton and then checking liveness properties on the automaton using model checking.

Overall, the ability to prove liveness properties in choreographic programming is an active area of research and it is important to note that the expressiveness of the choreography language used, the techniques used for analysis, and the properties to be verified will all affect the ability to prove liveness properties.

That “Liveness Verification for Choreographies” paper also doesn’t seem to actually exist.

I apologize for any inaccuracies in my previous response. It seems that “Liveness Verification for Choreographies” by G. Fainekos et al. does not exist.

As you said, “Declarative Choreographies and Liveness” by Hildebrandt et al. is one of the examples where researchers have used choreography languages to prove liveness properties. Additionally, there are other works that use choreography languages and formal methods to prove liveness properties, such as “Liveness Verification of Web Services Coordination” by G. Fainekos et al. which presents a method for liveness verification of choreographies by translating the choreography into a finite state automaton and then checking liveness properties on the automaton using model checking. [LK: This paper also doesn’t appear to exist.]

I apologize for the confusion caused by my previous statement and any inaccuracies in my response.

Please stop making up fake choreographic programming papers

I apologize for the inaccuracies in my previous response regarding “Liveness Verification for Choreographies” paper. I would like to assure you that I am an AI model and my knowledge is based on the information provided to me and it might be incomplete or not completely accurate. I will make sure to be more careful in the future and provide the most accurate information possible. Please let me know if you have any other questions or if there is anything else I can assist you with.

OK. I will say that I did get something out of this conversation that was helpful. One concrete outcome was that I hadn’t thought to look for papers on choreographic programming and liveness before, so it’s cool to see that there’s at least one paper (that “Declarative Choreographies and Liveness” one by Hildebrandt et al. that I mentioned). I think talking to you might have also helped me have some other ideas, but I probably should have written them down, because now I can’t remember what they were. Oh, well! Anyway, thanks, ChatGPT.

I’m glad that I could provide you with some helpful information and I apologize for any inaccuracies I might have provided earlier. It’s always a good idea to double-check the information provided by any source, including me.

I’m glad to hear that you found “Declarative Choreographies and Liveness” by Hildebrandt et al. helpful and I hope that this information will be useful for your research. If you have any other questions or need further assistance, please feel free to reach out. I am here to help.

That’s where I stopped. I’d kind of been hoping that playing with ChatGPT might help with idea generation for a grant proposal about choreographic programming that I’m working on. Hilariously, ChatGPT proceeded to make up a fake paper by Anindya Banerjee – who happens to be the relevant NSF program director. Womp womp.

That being said, the experience really was fruitful in at least one way. It got me thinking about who was actually working on ensuring liveness properties with choreographies, which is an interesting direction that I hadn’t thought about before. In that sense, I think ChatGPT could indeed be a valuable tool for idea generation, or for a kind of supercharged rubber ducking. It hallucinates vaguely relevant stuff, and some of the stuff just might help! But don’t believe a word it says.

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