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Despite some experience with Lisp and ML, I'm having a great deal of trouble learning to read and (idiomatically) write Haskell because the local style seems to be
do eta elimination whenever possible
eschew parentheses in favor of exploiting operator precedence
pack half your logic into bucketloads of overloaded, non-alphanumeric infix operators
The last one is particularly difficult because there are so many predefined operators, each with their own conventions and general semantics, that often reading Haskell becomes an exercise in Hoogle and :type.
Are there any good tutorials that assume knowledge of CS/functional concepts, and instead focus on Haskell-specific idioms? I'm looking for something like Real-World Haskell, that starts off with a very naive, explicit program and then gradually transforms it into a more idiomatic style, introducing and explaining the idioms as it goes. But instead of introducing and explaining general concepts like monads and type classes, it would introduce specific monads and specific type classes, like "but this is exactly what the Alternative monoid does!"
Basic type classes like Show, Eq and Ord should be easy to grasp by reading the library documentation found by Hoogle and/or Haskell-2010 Language Report.
The numeric tower in Haskell seems to be convoluted (Int type is an instance of whooping 11 type classes according to the report), but it is just to support all useful kinds of numbers and number representations mathematicians invented for us: e.g. Integer is a arbitrary size integer, Int is usual machine word-sized integer, and a lazy Peano representation of integers (not in standard library) proved useful in implementation of graph algorithms. The most important numeric type classes are Num and Integral. You can convert between different integer types by using fromIntegral functions. Note also that numerals such as 123 have type Num a => a and there's special type defaulting mechanism designed to reduce the need of type declarations to specify exact numeric type you need. In advanced use cases this works against you so you may want to alter the defaults.
The same situation is with different types of strings: no single representation fits all, so many of them are in the wild: String, Data.ByteString and Data.Text are most important.
Regarding more complicated type classes the best source is Typeclassopedia.
For certain type classes such as Monad, Applicative and Arrow there are a lot of dedicated tutorials and research works. Depending on your math skills, you may also want to read original research papers on the category theory concepts behind the type classes such as excellent "Notions of computation and monads" by Eugenio Moggi.
As for "eta reductions" it is called Point-Free Style. You can get some information from
the references mentioned at that link. You can also look at Combinatory Logic, a 1978 paper by John Backus Can programming be liberated from von neumann style? and APL programming language to get a richer historical perspective on the point-free style.
Also there are general books on Haskell such as 'A Gentle Introduction to Haskell' and 'Learn You a Haskell for Great Good'.
As for operator precedence - there are really few operators you must remember: (.), ($) and (>>=) are used much more than everything else (barring arithmetics of course but arithmetic operators are rather unsurprising).
The syntax for tuples and lists seems unproblematic for me too. It is just redundant: foo : bar : [] is the same as [foo, bar] and (,) foo bar is the same as (foo, bar). The prefix versions of tuples of higher arity such as (,,,,) are rarely used.
See also http://www.haskell.org/haskellwiki/Section_of_an_infix_operator for explanation of constructs such as (+ 2) and (2 +) called sections.
Also you can learn from the changes the HLint tool suggests to improve your code. The HLint executable can be installed by cabal install HLint.
As for advanced topics, I can recommend studying purely functional data structures (lets you design efficient immutable data structures and reason about time consumption), call by need lambda calculus (lets you reason about what is evaluated and in which order), System Fc type system (gives you some background on how haskell type checker works), denotational semantic (reasoning about non-termination, partiality and recursion, and also some insight on the notions of strictness, purity and composability).
I think the "Write Yourself a Scheme in 48 Hours" tutorial is exactly what you're looking for. This tutorial explains how to implement a Scheme interpreter in Haskell; it's the one document that really made everything click for me.
It has concrete examples of various Haskell idioms and ideas all rolled together in a cool project. This is particularly good for somebody with experience in Lisp, especially if you've read something like SICP or have implemented a Scheme interpreter before. The tutorial is great either way, but it might be a little bit easier to follow if you've done something similar before.
OK, for those who have never encountered the term, a quine is a "self-replicating" computer program. To be more specific, one which - upon execution - produces a copy of its own source code as its only output.
The quines can, of course, be developed in many programming languages (but not all); but some languages are obviously more suited to producing quines than others (to clearly understand the somewhat subjective-sounding "more suited", look at a Haskell example vs. C example in the Wiki page - and I provide my more-objective definition below).
The question I have is, from programming language perspective, what language features (either theoretical design ones or syntax sugar) make the language more suitable/helpful for writing quines?
My definition of "more suitable" is "quines are easier to write" and "are shorter/more readable/less obfuscated". But you're welcome to add more criteria that are at least somewhat objective.
Please note that this question explicitly excludes degenerate cases, like a language which is designed to contain "print_a_quine" primitive.
I am not entirely sure, so correct me if anyone of you knows better.
I agree with both other answers, going further by explaining, that a quine is this:
Y g
where Y is a Y fixed-point combinator (or any other fixed-point combinator), which means in lambda calculus:
Y g = g(Y g)
now, it is quite apparent, that we need the code to be data and g be a function which will print its arguments.
So to summarize we need for constructing such a quines functions, printing function, fixed-point combinator and call-by-name evaluation strategy.
The smallest language that satisfies this conditions is AFAIK Zot from the Iota and Jot family.
Languages like the Io Programming Language and others allow the treating of code as data. In tree walking systems, this typically allows the language implementer to expose the abstract syntax tree as a first class citizen. In the case of Io, this is what it does. Being object oriented, the AST is modelled around Message objects, and a special sentinel is created to represent the currently executing message; this sentinel is called thisMessage. thisMessage is a full Message like any other, and responds to the print message, which prints it to the screen. As a result, the shortest quine I've ever been able to produce in any language, has come from Io and looks like this:
thisMessage print
Anyway, I just couldn't help but sharing this with you on this subject. The above certainly makes writing quines easy, but not doing it this way certainly doesn't preclude easily creating a quine.
I'm not sure if this is useful answer from a practical point of view, but there is some useful theory in computability theory. In particular fixed points and Kleene's recursion theorem can be used for writing quines. Apparently, the theory can be used for writing quine in LISP (as the wikipedia page shows).
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As far as I can see, the usual (and best in my opinion) order for teaching iterting constructs in functional programming with Scheme is to first teach recursion and maybe later get into things like map, reduce and all SRFI-1 procedures. This is probably, I guess, because with recursion the student has everything that's necessary for iterating (and even re-write all of SRFI-1 if he/she wants to do so).
Now I was wondering if the opposite approach has ever been tried: use several procedures from SRFI-1 and only when they are not enough (for example, to approximate a function) use recursion. My guess is that the result would not be good, but I'd like to know about any past experiences with this approach.
Of course, this is not specific to Scheme; the question is also valid for any functional language.
One book that teaches "applicative programming" (the use of combinators) before recursion is Dave Touretsky's COMMON LISP: A Gentle Introduction to Symbolic Computation -- but then, it's a Common Lisp book, and he can teach imperative looping before that.
IMO starting with basic blocks of knowledge first is better, then derive the results. This is what they do in mathematics, i.e. they don't introduce exponentiation before multiplication, and multiplication before addition because the former in each case is derived from the latter. I have seen some instructors go the other way around, and I believe it is not as successful like when you go from the basics to the results. In addition, by delaying the more advanced topics, you give students a mental challenge to derive these results them selves using the knowledge they already have.
There is something fundamentally flawed in saying "with recursion the student has everything that's necessary for iterating". It's true that when you know how to write (recursive) functions you can do anything, but what is that better for a student? When you think about it, you also have everything you need if you know machine language, or to make a more extreme point, if I give you a cpu and a pile of wires.
Yes, that's an over-exaggeration, but it can relate to the way people teach. Take any language and remove any inessential constructs -- at the extreme of doing so in a functional language like Scheme, you'll be left with the lambda calculus (or something similar), which -- again -- is everything that you need. But obviously you shouldn't throw beginners into that pot before you cover more territory.
To put this in more concrete perspective, consider the difference between a list and a pair, as they are implemented in Scheme. You can do a lot with just lists even if you know nothing about how they're implemented as pairs. In fact, if you give students a limited form of cons that requires a proper list as its second argument then you'll be doing them a favor by introducing a consistent easier-to-grok concept before you proceed to the details of how lists are implemented. If you have experience teaching this stuff, then I'm sure that you've encountered many students that get hopelessly confused over using cons where the want append and vice versa. Problems that require both can be extremely difficult to newbies, and all the box+pointer diagrams in the world are not going to help them.
So, to give an actual suggestion, I recommend you have a look at HtDP: one of the things that this book is doing very carefully is to expose students gradually to programming, making sure that the mental picture at every step is consistent with what the student knows at that point.
I have never seen this order used in teaching, and I find it as backwards as you. There are quite a few questions on StackOverflow that show that at least some programmers think "functional programming" is exclusively the application of "magic" combinators and are at a loss when the combinator they need doesn't exist, even if what they would need is as simple as map3.
Considering this bias, I would make sure that students are able to write each combinator themselves before introducing it.
I also think introducing map/reduce before recursion is a good idea. (However, the classic SICP introduces recursion first, and implement map/reduce based on list and recursion. This is a building abstraction from bottom up approach. Its emphises is still abstraction.)
Here's the sum-of-squares example I can share with you using F#/ML:
let sumOfSqrs1 lst =
let rec sum lst acc =
match lst with
| x::xs -> sum xs (acc + x * x)
| [] -> acc
sum lst 0
let sumOfSqr2 lst =
let sqr x = x * x
lst |> List.map sqr |> List.sum
The second method is a more abstract way to do this sum-of-squares problem, while the first one expresses too much details. The strength of functional programming is better abstraction. The second program using the List library expresses the idea that the for loop can be abstracted out.
Once the student could play with List.*, they would be eager to know how these functions are implemented. At that time, you could go back to recursion. This is kind of top-down teaching approach.
I think this is a bad idea.
Recursion is one of the hardest basic subjects in programming to understand, and even harder to use. The only way to learn this is to do it, and a lot of it.
If the students will be handed the nicely abstracted higher order functions, they will use these over recursion, and will just use the higher order functions. Then when they will need to write a higher order function themselves, they will be clueless and will need you, the teacher, to practically write the code for them.
As someone mentioned, you've gotta learn a subject bottom-up if you want people to really understand a subject and how to customize it to their needs.
I find that a lot of people when programming functionally often 'imitate' an imperative style and try to imitate loops with recursion when they don't need anything resembling a loop and need map or fold/reduce instead.
Most functional programmers would agree that you shouldn't try to imitate an imperative style, I think recursion shouldn't be 'taught' at all, but should develop naturally and self-explanatory, in declarative programming it's often at various points evident that a function is defined in terms of itself. Recursion shouldn't be seen as 'looping' but as 'defining a function in terms of itself'.
Map however is a repetition of the same thing all over again, often when people use (tail) recursion to simulate loops, they should be using map in functional style.
The thing is that the "recursion" you really want to teach/learn is, ultimately, tail recursion, which is technically not recursion but a loop.
So I say go ahead and teach/learn the real recursion (the one nobody uses in real-life because it's impractical), then teach why they are useless, then teach tail-recursion, then teach why they are not recursions.
That seems to me to be the best way. If you're learning, do all this before using higher-order functions too much. If you're teaching, show them how they replace loops (and then they'll understand later when you teach tail-recursion how the looping is really just hidden but still there).
I recently started studying functional programming using Haskell and came upon this article on the official Haskell wiki: How to read Haskell.
The article claims that short variable names such as x, xs, and f are fitting for Haskell code, because of conciseness and abstraction. In essence, it claims that functional programming is such a distinct paradigm that the naming conventions from other paradigms don't apply.
What are your thoughts on this?
In a functional programming paradigm, people usually construct abstractions not only top-down, but also bottom-up. That means you basically enhance the host language. In this kind of situations I see terse naming as appropriate. The Haskell language is already terse and expressive, so you should be kind of used to it.
However, when trying to model a certain domain, I don't believe succinct names are good, even when the function bodies are small. Domain knowledge should reflect in naming.
Just my opinion.
In response to your comment
I'll take two code snippets from Real World Haskell, both from chapter 3.
In the section named "A more controlled approach", the authors present a function that returns the second element of a list. Their final version is this:
tidySecond :: [a] -> Maybe a
tidySecond (_:x:_) = Just x
tidySecond _ = Nothing
The function is generic enough, due to the type parameter a and the fact we're acting on a built in type, so that we don't really care what the second element actually is. I believe x is enough in this case. Just like in a little mathematical equation.
On the other hand, in the section named "Introducing local variables", they're writing an example function that tries to model a small piece of the banking domain:
lend amount balance = let reserve = 100
newBalance = balance - amount
in if balance < reserve
then Nothing
else Just newBalance
Using short variable name here is certainly not recommended. We actually do care what those amounts represent.
I think if the semantics of the arguments are clear within the context of the code then you can get away with short variable names. I often use these in C# lambdas for the same reason. However if it is ambiguous, you should be more explicit with naming.
map :: (a->b) -> [a] -> [b]
map f [] = []
map f (x:xs) = f x : map f xs
To someone who hasn't had any exposure to Haskell, that might seem like ugly, unmaintainable code. But most Haskell programmers will understand this right away. So it gets the job done.
var list = new int[] { 1, 2, 3, 4, 5 };
int countEven = list.Count(n => n % 2 == 0)
In that case, short variable name seems appropriate.
list.Aggregate(0, (total, value) => total += value);
But in this case it seems more appropriate to name the variables, because it isn't immediately apparent what the Aggregate is doing.
Basically, I believe not to worry too much about convention unless it's absolutely necessary to keep people from screwing up. If you have any choice in the matter, use what makes sense in the context (language, team, block of code) you are working, and will be understandable by someone else reading it hours, weeks or years later. Anything else is just time-wasting OCD.
I think scoping is the #1 reason for this. In imperative languages, dynamic variables, especially global ones need to be named properly, as they're used in several functions. With lexical scoping, it's clear what the symbol is bound to at compile time.
Immutability also contributes to this to some extent- in traditional languages like C/ C++/ Java, a variable can represent different data at different points in time. Therefore, it needs to be given a name to give the programmer an idea of its functionality.
Personally, I feel that features features like first-class functions make symbol names pretty redundant. In traditional languages, it's easier to relate to a symbol; based on its usage, we can tell if it's data or a function.
I'm studying Haskell now, but I don't feel that its naming conventions is so very different. Of course, in Java you're hardly to find a names like xs. But it is easy to find names like x in some mathematical functions, i, j for counters etc. I consider such names to be perfectly appropriate in right context. xs in Haskell is appropriate only generic functions over lists. There's a lot of them in Haskell, so this name is wide-spread. Java doesn't provide easy way to handle such a generic abstractions, that's why names for lists (and lists themselves) are usually much more specific, e.g. lists or users.
I just attended a number of talks on Haskell with lots of code samples. As longs as the code dealt with x, i and f the naming didn't bother me. However, as soon as we got into heavy duty list manipulation and the like I found the three letters or so names to be a lot less readable than I prefer.
To be fair a significant part of the naming followed a set of conventions, so I assume that once you get into the lingo it will be a little easier.
Fortunately, nothing prevents us from using meaningful names, but I don't agree that the language itself somehow makes three letter identifiers meaningful to the majority of people.
When in Rome, do as the Romans do
(Or as they say in my town: "Donde fueres, haz lo que vieres")
Anything that aids readability is a good thing - meaningful names are therefore a good thing in any language.
I use short variable names in many languages but they're reserved for things that aren't important in the overall meaning of the code or where the meaning is clear in the context.
I'd be careful how far I took the advice about Haskell names
My Haskell practice is only of mediocre level, thus, I dare to try to reply only the second, more general part of Your question:
"In essence, it claims that functional programming is such a distinct paradigm that the naming conventions from other paradigms don't apply."
I suspect, the answer is "yes", but my motivation behind this opinion is restricted only on experience in just one single functional language. Still, it may be interesting, because this is an extremely minimalistic one, thus, theoretically very "pure", and underlying a lot of practical functional languages.
I was curios how easy it is to write practical programs on such an "extremely" minimalistic functional programming language like combinatory logic.
Of course, functional programming languages lack mutable variables, but combinatory logic "goes further one step more" and it lacks even formal parameters. It lacks any syntactic sugar, it lacks any predefined datatypes, even booleans or numbers. Everything must be mimicked by combinators, and traced back to the applications of just two basic combinators.
Despite of such extreme minimalism, there are still practical methods for "programming" combinatory logic in a neat and pleasant way. I have written a quine in it in a modular and reusable way, and it would not be nasty even to bootstrap a self-interpreter on it.
For summary, I felt the following features in using this extremely minimalistic functional programming language:
There is a need to invent a lot of auxiliary functions. In Haskell, there is a lot of syntactic sugar (pattern matching, formal parameters). You can write quite complicated functions in few lines. But in combinatory logic, a task that could be expressed in Haskell by a single function, must be replaced with well-chosen auxiliary functions. The burden of replacing Haskell syntactic sugar is taken by cleverly chosen auxiliary functions in combinatory logic. As for replying Your original question: it is worth of inventing meaningful and catchy names for these legions of auxiliary functions, because they can be quite powerful and reusable in many further contexts, sometimes in an unexpected way.
Moreover, a programmer of combinatory logic is not only forced to find catchy names of a bunch of cleverly chosen auxiliary functions, but even more, he is forced to (re)invent whole new theories. For example, for mimicking lists, the programmer is forced to mimick them with their fold functions, basically, he has to (re)invent catamorphisms, deep algebraic and category theory concepts.
I conjecture, several differences can be traced back to the fact that functional languages have a powerful "glue".
In Haskell, meaning is conveyed less with variable names than with types. Being purely functional has the advantage of being able to ask for the type of any expression, regardless of context.
I agree with a lot of the points made here about argument naming but a quick 'find on page' shows that no one has mentioned Tacit programming (aka pointfree / pointless). Whether this is easier to read may be debatable so it's up to you & your team, but definitely worth a thorough consideration.
No named arguments = No argument naming conventions.
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I'm going to be teaching a lower-division course in discrete structures. I have selected the text book Discrete Structures, Logic, and Computability in part because it contains examples and concepts that are conducive to implementation with a functional programming language. (I also think it's a good textbook.)
I want an easy-to-understand FP language to illustrate DS concepts and that the students can use. Most students will have had only one or two semesters of programming in Java, at best. After looking at Scheme, Erlang, Haskell, Ocaml, and SML, I've settled on either Haskell or Standard ML. I'm leaning towards Haskell for the reasons outlined below, but I'd like the opinion of those who are active programmers in one or the other.
Both Haskell and SML have pattern matching which makes describing a recursive algorithm a cinch.
Haskell has nice list comprehensions that match nicely with the way such lists are expressed mathematically.
Haskell has lazy evaluation. Great for constructing infinite lists using the list comprehension technique.
SML has a truly interactive interpreter in which functions can be both defined and used. In Haskell, functions must be defined in a separate file and compiled before being used in the interactive shell.
SML gives explicit confirmation of the function argument and return types in a syntax that's easy to understand. For example: val foo = fn : int * int -> int. Haskell's implicit curry syntax is a bit more obtuse, but not totally alien. For example: foo :: Int -> Int -> Int.
Haskell uses arbitrary-precision integers by default. It's an external library in SML/NJ. And SML/NJ truncates output to 70 characters by default.
Haskell's lambda syntax is subtle -- it uses a single backslash. SML is more explicit. Not sure if we'll ever need lambda in this class, though.
Essentially, SML and Haskell are roughly equivalent. I lean toward Haskell because I'm loving the list comprehensions and infinite lists in Haskell. But I'm worried that the extensive number of symbols in Haskell's compact syntax might cause students problems. From what I've gathered reading other posts on SO, Haskell is not recommended for beginners starting out with FP. But we're not going to be building full-fledged applications, just trying out simple algorithms.
What do you think?
Edit: Upon reading some of your great responses, I should clarify some of my bullet points.
In SML, there's no syntactic distinction between defining a function in the interpreter and defining it in an external file. Let's say you want to write the factorial function. In Haskell you can put this definition into a file and load it into GHCi:
fac 0 = 1
fac n = n * fac (n-1)
To me, that's clear, succinct, and matches the mathematical definition in the book. But if you want to write the function in GHCi directly, you have to use a different syntax:
let fac 0 = 1; fac n = n * fac (n-1)
When working with interactive interpreters, from a teaching perspective it's very, very handy when the student can use the same code in both a file and the command line.
By "explicit confirmation of the function," I meant that upon defining the function, SML right away tells you the name of the function, the types of the arguments, and the return type. In Haskell you have to use the :type command and then you get the somewhat confusing curry notation.
One more cool thing about Haskell -- this is a valid function definition:
fac 0 = 1
fac (n+1) = (n+1) * fac n
Again, this matches a definition they might find in the textbook. Can't do that in SML!
Much as I love Haskell, here are the reasons I would prefer SML for a class in discrete math and data structures (and most other beginners' classes):
Time and space costs of Haskell programs can be very hard to predict, even for experts. SML offers much more limited ways to blow the machine.
Syntax for function defintion in an interactive interpreter is identical to syntax used in a file, so you can cut and paste.
Although operator overloading in SML is totally bogus, it is also simple. It's going to be hard to teach a whole class in Haskell without having to get into type classes.
Student can debug using print. (Although, as a commenter points out, it is possible to get almost the same effect in Haskell using Debug.Trace.trace.)
Infinite data structures blow people's minds. For beginners, you're better off having them define a stream type complete with ref cells and thunks, so they know how it works:
datatype 'a thunk_contents = UNEVALUATED of unit -> 'a
| VALUE of 'a
type 'a thunk = 'a thunk_contents ref
val delay : (unit -> 'a) -> 'a thunk
val force : 'a thunk -> 'a
Now it's not magic any more, and you can go from here to streams (infinite lists).
Layout is not as simple as in Python and can be confusing.
There are two places Haskell has an edge:
In core Haskell you can write a function's type signature just before its definition. This is hugely helpful for students and other beginners. There just isn't a nice way to deal with type signatures in SML.
Haskell has better concrete syntax. The Haskell syntax is a major improvement over ML syntax. I have written a short note about when to use parentheses in an ML program; this helps a little.
Finally, there is a sword that cuts both ways:
Haskell code is pure by default, so your students are unlikely to stumble over impure constructs (IO monad, state monad) by accident. But by the same token, they can't print, and if you want to do I/O then at minumum you have to explain do notation, and return is confusing.
On a related topic, here is some advice for your course preparation: don't overlook Purely Functional Data Structures by Chris Okasaki. Even if you don't have your students use it, you will definitely want to have a copy.
We teach Haskell to first years at our university. My feelings about this are a bit mixed. On the one hand teaching Haskell to first years means they don't have to unlearn the imperative style. Haskell can also produce very concise code which people who had some Java before can appreciate.
Some problems I've noticed students often have:
Pattern matching can be a bit difficult, at first. Students initially had some problems seeing how value construction and pattern matching are related. They also had some problems distinguishing between abstractions. Our exercises included writing functions that simplify arithmetic expression and some students had difficulty seeing the difference between the abstract representation (e.g., Const 1) and the meta-language representation (1).
Furthermore, if your students are supposed to write list processing functions themselves, be careful pointing out the difference between the patterns
[]
[x]
(x:xs)
[x:xs]
Depending on how much functional programming you want to teach them on the way, you may just give them a few library functions and let them play around with that.
We didn't teach our students about anonymous functions, we simply told them about where clauses. For some tasks this was a bit verbose, but worked well otherwise. We also didn't tell them about partial applications; this is probably quite easy to explain in Haskell (due to its form of writing types) so it might be worth showing to them.
They quickly discovered list comprehensions and preferred them over higher-order functions like filter, map, zipWith.
I think we missed out a bit on teaching them how to let them guide their thoughts by the types. I'm not quite sure, though, whether this is helpful to beginners or not.
Error messages are usually not very helpful to beginners, they might occasionally need some help with these. I haven't tried it myself, but there's a Haskell compiler specifically targeted at newcomers, mainly by means of better error messages: Helium
For the small programs, things like possible space leaks weren't an issue.
Overall, Haskell is a good teaching language, but there are a few pitfalls. Given that students feel a lot more comfortable with list comprehensions than higher-order functions, this might be the argument you need. I don't know how long your course is or how much programming you want to teach them, but do plan some time for teaching them basic concepts--they will need it.
BTW,
# SML has a truly interactive
interpreter in which functions can be
both defined and used. In Haskell,
functions must be defined in a
separate file and compiled before
being used in the interactive shell.
Is inaccurate. Use GHCi:
Prelude> let f x = x ^ 2
Prelude> f 7
49
Prelude> f 2
4
There are also good resources for Haskell in education on the haskell.org edu. page, with experiences from different teachers. http://haskell.org/haskellwiki/Haskell_in_education
Finally, you'll be able to teach them multicore parallelism just for fun, if you use Haskell :-)
Many universities teach Haskell as a first functional language or even a first programming language, so I don't think this will be a problem.
Having done some of the teaching on one such course, I don't agree that the possible confusions you identify are that likely. The most likely sources of early confusion are parsing errors caused by bad layout, and mysterious messages about type classes when numeric literals are used incorrectly.
I'd also disagree with any suggestion that Haskell is not recommended for beginners starting out with FP. It's certainly the big bang approach in ways that strict languages with mutation aren't, but I think that's a very valid approach.
SML has a truly interactive interpreter in which functions can be both defined and used. In Haskell, functions must be defined in a separate file and compiled before being used in the interactive shell.
While Hugs may have that limitation, GHCi does not:
$ ghci
GHCi, version 6.10.1: http://www.haskell.org/ghc/ :? for help
Loading package ghc-prim ... linking ... done.
Loading package integer ... linking ... done.
Loading package base ... linking ... done.
Prelude> let hello name = "Hello, " ++ name
Prelude> hello "Barry"
"Hello, Barry"
There's many reasons I prefer GHC(i) over Hugs, this is just one of them.
SML gives explicit confirmation of the function argument and return types in a syntax that's easy to understand. For example: val foo = fn : int * int -> int. Haskell's implicit curry syntax is a bit more obtuse, but not totally alien. For example: foo :: Int -> Int -> Int.
SML has what you call "implicit curry" syntax as well.
$ sml
Standard ML of New Jersey v110.69 [built: Fri Mar 13 16:02:47 2009]
- fun add x y = x + y;
val add = fn : int -> int -> int
Essentially, SML and Haskell are roughly equivalent. I lean toward Haskell because I'm loving the list comprehensions and infinite lists in Haskell. But I'm worried that the extensive number of symbols in Haskell's compact syntax might cause students problems. From what I've gathered reading other posts on SO, Haskell is not recommended for beginners starting out with FP. But we're not going to be building full-fledged applications, just trying out simple algorithms.
I like using Haskell much more than SML, but I would still teach SML first.
Seconding nominolo's thoughts, list comprehensions do seem to slow students from getting to some higher-order functions.
If you want laziness and infinite lists, it's instructive to implement it explicitly.
Because SML is eagerly evaluated, the execution model is far easier to comprehend, and "debugging via printf" works a lot better than in Haskell.
SML's type system is also simpler. While your class likely wouldn't use them anyways, Haskell's typeclasses are still an extra bump to get over -- getting them to understand the 'a versus ''a distinction in SML is tough enough.
Most answers were technical, but I think you should consider at least one that is not: Haskell (as OCaml), at this time, has a bigger community using it in a wider range of contexts. There's also a big database of libraries and applications written for profit and fun at Hackage. That may be an important factor in keeping some of your students using the language after your course is finished, and maybe trying other functional languages (like Standard ML) later.
I am amazed you are not considering OCaml and F# given that they address so many of your concerns. Surely decent and helpful development environments are a high priority for learners? SML is way behind and F# is way ahead of all other FPLs in that respect.
Also, both OCaml and F# have list comprehensions.
Haskell. I'm ahead in my algos/theory class in CS because of the stuff I learned from using Haskell. It's such a comprehensive language, and it will teach you a ton of CS, just by using it.
However, SML is much easier to learn. Haskell has features such as lazy evaluation and control structures that make it much more powerful, but with the cost of a steep(ish) learning curve. SML has no such curve.
That said, most of Haskell was unlearning stuff from less scientific/mathematic languages such as Ruby, ObjC, or Python.