This proposal defines *immutable* data structures for queues, sets, and maps. A structure is immutable when all its operations leave the structure unchanged. Note that none of the procedures specified here ends with a !.

Immutable structures are sometimes called *persistent* and are closely related to *pure-functional* (a.k.a. *pure*) structures. The availability of immutable data structures facilitates writing efficient programs in the pure-functional style.

We specify required time efficiency upper bounds using big-O notation. We note when, in some cases, there is "slack" between the required bound and the theoretically optimal bound for an operation. Implementations may use data structures with amortized time bounds, but should document which bounds hold in only an amortized sense. The use of randomized data structures with expected time bounds is discouraged.

A deque (conventionally pronounced "deck") is a queue data structure that supports efficient manipulation of either of its ends. It may be used in place of a (LIFO) stack or (FIFO) queue.

The *unlabeled finger tree* data structure can meet all these requirements rather conveniently.

Create a new deque containing element.... The leftmost element (if any) will be at the front of the deque and the rightmost element (if any) will be at the back. Takes O(n) time, where n is the number of elements.

ideque?}}} and {{{ideque-empty?}}} take O(1) time; {{{ideque-length may take O(n) time, though O(1) is optimal.

Return the front/back element. It is an error for deque to be empty. Each takes O(1) time.

(ideque-pop-front deque) (ideque-pop-back deque)Return a new deque with the front/back element removed. It is an error for deque to be empty. Each takes O(1) time.

(ideque-push-front deque x) (ideque-push-back deque x)Return a new deque with x}}} pushed to the front/back of {{{deque. Each takes O(1) time.

Return a new deque with the contents of the first argument deque followed by the others. Takes O(kn) time, where k is the number of deques and n is the number of elements involved, though O(k log n) is possible.

Conversion between deque and list structures. FIFO order is preserved, so the front of a list corresponds to the front of a deque. Each operation takes O(n) time.

A sorted set data structure stores a finite collection of unique orderable (a.k.a. comparable or sortable) elements.

These requirements can be satisfied by many flavors of *self-balancing binary trees.* Red-black trees, 1-2 brother trees, and labeled 2-3 finger trees are particularly convenient in an immutable context.

An *order predicate* for a universe of orderable elements is a procedure precedes?}}} such that, for set elements of the universe {{{x}}} and {{{y,

returns non-#false}}} iff {{{x}}} precedes {{{y}}} in the set's ordering. It returns {{{#false}}} when {{{x}}} succeeds (comes after) {{{y or when the elements are tied for the same position.

It is essential that order predicates return #false in the case of equal elements, as implementations may test for element equality with expressions of the form

(and (not (precedes? x y)) (not (precedes? y x)))Note that <}}}, {{{char<?}}}, and {{{string<? are valid order predicates for sets of numbers, characters, and strings, respectively.

The time bounds stated below are all based on the assumption that evaluating an order predicate takes O(1) time.

All elements of a set must be unique, which complicates operations that produce sets from collections that may contain duplicates. The procedures described consintely follow a *least recently used* removal policy. That means that, when an operation encounters two elements that are equal according to the order predicate, the one that was encountered earlier is removed from the set and replaced with the element that was encountered later.

Return a new set using the order predicate precedes?}}} and containing elements {{{element...}}}. If any elements are equal according to {{{precedes?, only the rightmost of them is retained. O(n log n) time.

iset-size may take O(n) time, though O(1) is optimal. The other procedures take O(1) time.

Return a new set containing the union/intersection/difference/symmetric difference of the arguments. All the arguments must be sets sharing an equivalent order predicate. The set operator is applied in a left-associative order. When an element is a member of multiple arguments to set-union, the object from the rightmost argument is retained. May take O(kn log n) time, where k is the number of sets and n is the number of elements involved, though O(kn) time is optimal.

Returns non-#false}}} iff {{{x}}} is an element of {{{set}}}, or {{{#false otherwise. Takes O(log n) time.

(iset-min set) (iset-max set)Returns the least/greatest element of set}}}. It is an error for {{{set to be empty. Takes O(log n) time; O(1) is optimal.

A continuation-based universal update procedure. Attempts to find an element match}}} equal to {{{x}}} in {{{set}}} according to the order predicate. When such a {{{match is found, calls

(present-proc match update remove)which must either tail-call

(update new-element ret)to replace match}}} with {{{new-element, or tail-call

(remove ret)to remove match}}} from {{{set}}}. In either case {{{ret}}} will be one of the values returned from the enclosing {{{iset-update call.

When no such match}}} is found, {{{iset-update calls

(absent-proc insert ignore)which should either tail-call

(insert ret)to insert x}}} into {{{set, or else tail-call

(ignore ret)to leave set}}} unchanged. Again, {{{ret}}} will be returned from the enclosing {{{iset-update call.

In any case, iset-update returns

(values new-set ret)where new-set}}} is a set reflecting the indicated modification, if any; and {{{ret is the return value produced by one of the continuations. It runs in O(log n) time.

(This procedure is based on an analogous procedure for hash tables suggested by Alexey Radul and attributed to Taylor Campbell.)

(iset-find set x [absent-thunk])Returns the element match}}} equal to {{{x}}} in {{{set}}}, or the result of evaluating {{{(absent-thunk)}}} if no such element exists. If {{{absent-thunk}}} is unspecified then a default procedure that always returns {{{#false is used. Takes O(log n) time.

(iset-include set x) (iset-exclude set x)Return a new set that certainly does/doesn't include x}}}. {{{iset-include}}} may replace an object equal to {{{x}}} already in {{{set, if any. Each operation takes O(log n) time.

(iset-predecessor set x [absent-thunk]) (iset-successor set x [absent-thunk])Returns the element that immediately precedes/succeeds x}}} in {{{set}}}'s ordering. If no such element exists because {{{x}}} is the minimum/maximum element, or because {{{set}}} is empty, returns the result of evaluating {{{(absent-thunk)}}}. If {{{absent-thunk}}} is unspecified then a default procedure that always returns {{{#false is used. Takes O(log n) time.

Returns a new set containing the elements of set}}} in the interval between {{{least}}} and {{{most}}}. If {{{include-least}}}/{{{include-most}}} is non-{{{#false}}} then the result includes an element equal to {{{least}}}/{{{most respectively; otherwise those elements are not included. Takes O(k log k + log n) time, where n is the number of elements in the set and k is the number of elements returned; O(k + log n) is optimal.

(iset-range< set x) (iset-range<= set x) (iset-range= set x) (iset-range>= set x) (iset-range> set x)Returns a new set containing only the elements of set}}} that are less/less-or-equal/equal/greater-or-equal/greater than {{{x. Takes O(k log k + log n) time, where n is the number of elements in the set and k is the number of elements returned; O(k + log n) is optimal.

Note that since set elements are unique, iset-range= returns a set of at most one element.

Returns a new set containing only those elements x}}} for which {{{(predicate? x)}}} returns non-{{{#false. Takes O(n log n) time; O(n) is optimal.

(iset-fold proc base set)The fundamental set iterator. Equivalent to, but may be more efficient than,

(fold proc base (iset->ordered-list set))Takes O(n) time.

(iset-map/monotone proc set [precedes?])Returns a new set containing the elements (proc x)}}} for every {{{x}}} in {{{set}}}. {{{proc}}} must be a ''monotone'' unary procedure that preserves the order of set elements. Observe that mapping a set of unique elements with a monotone function yields a new set of unique elements, so element uniqueness follows from the monotonicity assumption. If {{{precedes?}}} is given, it is the order predicate of the new set; otherwise the new set uses the same order predicate as {{{set. Takes O(n) time.

(iset-map proc set [precedes?])As iset-map/monotone}}}, except the {{{proc is not required to be monotone. When multiple elements are mapped to the same value, only the value originating from the greatest unmapped element is retained. O(n log n) time.

Returns a list containing the elements of set in increasing order. O(n) time.

(ordered-list->iset precedes? list)Returns a set containing the elements of list}}} and using order predicate {{{precedes?}}}. It is an error for {{{list to be anything other than a proper list of elements in increasing order. O(n log n) time; O(n) is optimal.

(list->iset precedes? list)Returns a set containing the elements of list}}} and using order predicate {{{precedes?}}}. {{{list}}} must be a proper list, but may contain duplicates and need not be in order. When a subset of input elements are equal according to {{{precedes?, only the last occurrence is retained. O(n log n) time.

These procedures compare x}}} to {{{y}}} according to {{{set}}}'s order predicate and the conventional meaning of {{{<}}}, {{{=}}}, and {{{>.

A map data structure stores key-value associations from a set of keys with an order predicate to arbitrary value objects. It is an alternative to an association list or hash table, which also store key-value associations, but with different key constraints and efficiency guarantees.

In the same way that a list of key-value dotted pairs can implement an association list, a set of key-value dotted pairs can implement a map. Implementations may use this approach, or may implement a distinct data structure specific to maps.

The behavior and efficiency of these operations is the same as the analogous set procedures.

The behavior and efficiency of these operations is the same as the analogous set procedures.

The behavior and efficiency of these operations is the same as the analogous set procedures.

(imap-min-value map) (imap-max-value map)Returns the value associated with (imap-min-key map)}}} and {{{(imap-max-key map) respectively. O(log n) time; O(1) is optimal.

A continuation-based universal update procedure. Attempts to find a key key-match}}} equal to {{{key}}} in {{{set}}}. When such a {{{key-match is found, calls

(present-proc key-match value update remove)which must either tail-call

(update new-key new-value ret)to replace key}}} with {{{new-key}}} and the corresponding value with {{{new-value, or tail-call

(remove ret)to remove the assocition from map}}}. In either case {{{ret}}} will be one of the values returned from the enclosing {{{imap-update call.

When no such key-match}}} is found, {{{imap-update calls

(absent-proc insert ignore)which should either tail-call

(insert new-key value ret)to insert new-key}}} and {{{value}}} into {{{map, or else tail-call

(ignore ret)to leave map}}} unchanged. Again, {{{ret}}} will be returned from the enclosing {{{imap-update call.

In any case, imap-update returns

(values new-map ret)where new-map}}} is a new map reflecting the indicated modification, if any; and {{{ret is the return value produced by one of the continuations. O(log n) time.

(imap-find map key [absent-thunk])Returns the value associated with key}}} in {{{map}}}, or the result of evaluating {{{(absent-thunk)}}} if no such value exists. If {{{absent-thunk}}} is unspecified then a default procedure that always returns {{{#false is used. O(log n) time.

(imap-include map key value) (imap-exclude map key)Return a new set that certainly does/doesn't include an association from key}}}. {{{imap-include}}} will replace any prior association from {{{key}}} that might exist in {{{map. O(log n) time.

(imap-key-predecessor map key [absent-thunk]) (imap-key-successor map key [absent-thunk])The behavior and efficiency of these operations is the same as the analogous set procedures.

The behavior and efficiency of these operations is the same as the analogous set procedures. (Least and most are keys.)

(imap-range< map key) (imap-range<= map key) (imap-range= map key) (imap-range>= map key) (imap-range> map key)The behavior and efficiency of these operations is the same as the analogous set procedures.

Returns a new set containing only those associations for which (proc key value)}}} returns non-{{{#false. O(n log n) time; O(n) is optimal.

(imap-fold proc base map)The fundamental map iterator. Calls

(proc key value accum)successively to accumulate a value initialized to base. O(n) time.

(imap-map-values proc map)Returns a new map where each value is replaced with the result of evaluating

(proc key value)for that value's key. Takes O(n) time.

(imap-map/monotone proc map [precedes?])Returns a new map containing the association values returned by calls to

(proc key value)for each key-value association in map}}}. {{{proc}}} must return {{{(values new-key new-value)}}}. The key mapping must be a ''monotone,'' preserving the order and uniqueness of keys. The value mapping need not be monotone. If {{{precedes?}}} is given, it is the key order predicate of the new map; otherwise the new map uses the same order predicate as {{{map. Takes O(n) time.

(imap-map proc map [precedes?])As imap-map/monotone}}}, except the {{{proc}}} is not required to be monotone. When multiple keys are mapped to the same {{{new-key, only the association originating from the greatest pre-mapped key is retained. O(n log n) time.

Returns an association list containing the associations of map in increasing order by key. O(n) time.

(imap-keys map)Returns a set containing the keys of map. O(n log n) time; O(n) is optimal.

(imap-values map)Returns a list containing the values of map in increasing order by key. O(n) time.

(ordered-alist->imap precedes? alist)Returns a map containing the associations of alist}}} and using order predicate {{{precedes?}}}. It is an error for {{{list to be anything other than a proper association list in increasing order by key. O(n log n) time; O(n) is optimal.

(alist->imap precedes? alist)The behavior and efficiency of these operations is the same as the analogous set procedures.

The behavior and efficiency of these operations is the same as the analogous set procedures.

- Should there be an explicitly-immutable pair and list?
- "imap" is a name clash with the IMAP email protocol. Is this a dealbreaker?

To start with, I basically think this proposal is an excellent start, providing facilities that Scheme programmers should have easily available to them.

I think it is *very* important that these proposals all be fleshed out to something the size of SRFI 1 and SRFI 113. Users should not wind up choosing between one data structure and another by which one has a more convenient API. If the API is as consistent as possible in all proposals, it's a big win for usability. I do not mean that absolutely every SRFI 1 feature is needed (in particular, I don't see a need for association deque support), but that these APIs seem much too small to fit with the evolving style of the large language; in the words of the charter, to be "large enough to address the practical needs of mainstream software development". Keeping it uniform also helps with human-memory issues. See ContainerSrfiComparison for something close to what I have in mind.

I will be putting together a proposal for mutable deques (aka tconc lists) at some point, no doubt closely based on this proposal and SRFI 1.

Because deques are ordered, I suggest ideque-length for compatibility with length, vector-length, and string-length. Unordered types like sets and maps should have iset-size and imap-size. SRFI 113 and HashTablesCowan already adopt this convention.

It's premature to do so yet, but I think this proposal should be prepared to incorporate ComparatorsCowan when it becomes a draft SRFI. This would mean accepting comparators wherever a precedence (<) function is expected. I plan to convert SRFI 113, HashTablesCowan, and whatever we use for a sort package (which I hope will be a revitalized SRFI 32) to this style.

I'm not opposed to the LRU convention, but I'd like to see it justified. If I'm convinced, I'll adopt it for SRFI 113 too -- again, uniformity is a win. Currently the spec says nothing and the implementation uses first-addition-wins. Terminologically, I think it should be "least recently *added*" rather than "used", or better yet speak of a "most recently added retention policy" rather than a removal policy.

I prefer difference and xor to asymmetric-difference and symmetric-difference, on the lines of SRFI 1 and SRFI 113. Does it really make sense to XOR more or fewer than two sets? SRFI 113 assumes it does not.

I'm puzzled by the MUSTard of the update procedure. Why *must* one of the success continuations be called? What's the matter with just returning, if you decide not to update the set? Ditto, why *should* for the failure continuation? Finally, in R7RS style MUSTard applies only to the implementation, not to programmer responsibilities, which are generally expressed with "It is an error if" language.

I also think that the failure continuation should precede the success continuation, for consistency with HashTablesCowan and SRFI 69.

I need more justification on the element-comparison procedures.

Take a look at the explicit merger procedures of SRFI 113 for union and intersection.

I think immutable pairs/lists should be a separate proposal.

I don't think the imap/IMAP naming conflict is important at all.