theory Tactic
imports Base
begin
chapter {* Tactical reasoning *}
text {* Tactical reasoning works by refining an initial claim in a
backwards fashion, until a solved form is reached. A @{text "goal"}
consists of several subgoals that need to be solved in order to
achieve the main statement; zero subgoals means that the proof may
be finished. A @{text "tactic"} is a refinement operation that maps
a goal to a lazy sequence of potential successors. A @{text
"tactical"} is a combinator for composing tactics. *}
section {* Goals \label{sec:tactical-goals} *}
text {*
Isabelle/Pure represents a goal as a theorem stating that the
subgoals imply the main goal: @{text "A\<^sub>1 \<Longrightarrow> \<dots> \<Longrightarrow> A\<^sub>n \<Longrightarrow>
C"}. The outermost goal structure is that of a Horn Clause: i.e.\
an iterated implication without any quantifiers\footnote{Recall that
outermost @{text "\<And>x. \<phi>[x]"} is always represented via schematic
variables in the body: @{text "\<phi>[?x]"}. These variables may get
instantiated during the course of reasoning.}. For @{text "n = 0"}
a goal is called ``solved''.
The structure of each subgoal @{text "A\<^sub>i"} is that of a
general Hereditary Harrop Formula @{text "\<And>x\<^sub>1 \<dots>
\<And>x\<^sub>k. H\<^sub>1 \<Longrightarrow> \<dots> \<Longrightarrow> H\<^sub>m \<Longrightarrow> B"}. Here @{text
"x\<^sub>1, \<dots>, x\<^sub>k"} are goal parameters, i.e.\
arbitrary-but-fixed entities of certain types, and @{text
"H\<^sub>1, \<dots>, H\<^sub>m"} are goal hypotheses, i.e.\ facts that may
be assumed locally. Together, this forms the goal context of the
conclusion @{text B} to be established. The goal hypotheses may be
again arbitrary Hereditary Harrop Formulas, although the level of
nesting rarely exceeds 1--2 in practice.
The main conclusion @{text C} is internally marked as a protected
proposition, which is represented explicitly by the notation @{text
"#C"} here. This ensures that the decomposition into subgoals and
main conclusion is well-defined for arbitrarily structured claims.
\medskip Basic goal management is performed via the following
Isabelle/Pure rules:
\[
\infer[@{text "(init)"}]{@{text "C \<Longrightarrow> #C"}}{} \qquad
\infer[@{text "(finish)"}]{@{text "C"}}{@{text "#C"}}
\]
\medskip The following low-level variants admit general reasoning
with protected propositions:
\[
\infer[@{text "(protect)"}]{@{text "#C"}}{@{text "C"}} \qquad
\infer[@{text "(conclude)"}]{@{text "A\<^sub>1 \<Longrightarrow> \<dots> \<Longrightarrow> A\<^sub>n \<Longrightarrow> C"}}{@{text "A\<^sub>1 \<Longrightarrow> \<dots> \<Longrightarrow> A\<^sub>n \<Longrightarrow> #C"}}
\]
*}
text %mlref {*
\begin{mldecls}
@{index_ML Goal.init: "cterm -> thm"} \\
@{index_ML Goal.finish: "Proof.context -> thm -> thm"} \\
@{index_ML Goal.protect: "thm -> thm"} \\
@{index_ML Goal.conclude: "thm -> thm"} \\
\end{mldecls}
\begin{description}
\item @{ML "Goal.init"}~@{text C} initializes a tactical goal from
the well-formed proposition @{text C}.
\item @{ML "Goal.finish"}~@{text "ctxt thm"} checks whether theorem
@{text "thm"} is a solved goal (no subgoals), and concludes the
result by removing the goal protection. The context is only
required for printing error messages.
\item @{ML "Goal.protect"}~@{text "thm"} protects the full statement
of theorem @{text "thm"}.
\item @{ML "Goal.conclude"}~@{text "thm"} removes the goal
protection, even if there are pending subgoals.
\end{description}
*}
section {* Tactics\label{sec:tactics} *}
text {* A @{text "tactic"} is a function @{text "goal \<rightarrow> goal\<^sup>*\<^sup>*"} that
maps a given goal state (represented as a theorem, cf.\
\secref{sec:tactical-goals}) to a lazy sequence of potential
successor states. The underlying sequence implementation is lazy
both in head and tail, and is purely functional in \emph{not}
supporting memoing.\footnote{The lack of memoing and the strict
nature of SML requires some care when working with low-level
sequence operations, to avoid duplicate or premature evaluation of
results. It also means that modified runtime behavior, such as
timeout, is very hard to achieve for general tactics.}
An \emph{empty result sequence} means that the tactic has failed: in
a compound tactic expression other tactics might be tried instead,
or the whole refinement step might fail outright, producing a
toplevel error message in the end. When implementing tactics from
scratch, one should take care to observe the basic protocol of
mapping regular error conditions to an empty result; only serious
faults should emerge as exceptions.
By enumerating \emph{multiple results}, a tactic can easily express
the potential outcome of an internal search process. There are also
combinators for building proof tools that involve search
systematically, see also \secref{sec:tacticals}.
\medskip As explained before, a goal state essentially consists of a
list of subgoals that imply the main goal (conclusion). Tactics may
operate on all subgoals or on a particularly specified subgoal, but
must not change the main conclusion (apart from instantiating
schematic goal variables).
Tactics with explicit \emph{subgoal addressing} are of the form
@{text "int \<rightarrow> tactic"} and may be applied to a particular subgoal
(counting from 1). If the subgoal number is out of range, the
tactic should fail with an empty result sequence, but must not raise
an exception!
Operating on a particular subgoal means to replace it by an interval
of zero or more subgoals in the same place; other subgoals must not
be affected, apart from instantiating schematic variables ranging
over the whole goal state.
A common pattern of composing tactics with subgoal addressing is to
try the first one, and then the second one only if the subgoal has
not been solved yet. Special care is required here to avoid bumping
into unrelated subgoals that happen to come after the original
subgoal. Assuming that there is only a single initial subgoal is a
very common error when implementing tactics!
Tactics with internal subgoal addressing should expose the subgoal
index as @{text "int"} argument in full generality; a hardwired
subgoal 1 is not acceptable.
\medskip The main well-formedness conditions for proper tactics are
summarized as follows.
\begin{itemize}
\item General tactic failure is indicated by an empty result, only
serious faults may produce an exception.
\item The main conclusion must not be changed, apart from
instantiating schematic variables.
\item A tactic operates either uniformly on all subgoals, or
specifically on a selected subgoal (without bumping into unrelated
subgoals).
\item Range errors in subgoal addressing produce an empty result.
\end{itemize}
Some of these conditions are checked by higher-level goal
infrastructure (\secref{sec:struct-goals}); others are not checked
explicitly, and violating them merely results in ill-behaved tactics
experienced by the user (e.g.\ tactics that insist in being
applicable only to singleton goals, or prevent composition via
standard tacticals such as @{ML REPEAT}).
*}
text %mlref {*
\begin{mldecls}
@{index_ML_type tactic: "thm -> thm Seq.seq"} \\
@{index_ML no_tac: tactic} \\
@{index_ML all_tac: tactic} \\
@{index_ML print_tac: "string -> tactic"} \\[1ex]
@{index_ML PRIMITIVE: "(thm -> thm) -> tactic"} \\[1ex]
@{index_ML SUBGOAL: "(term * int -> tactic) -> int -> tactic"} \\
@{index_ML CSUBGOAL: "(cterm * int -> tactic) -> int -> tactic"} \\
\end{mldecls}
\begin{description}
\item Type @{ML_type tactic} represents tactics. The
well-formedness conditions described above need to be observed. See
also @{file "~~/src/Pure/General/seq.ML"} for the underlying
implementation of lazy sequences.
\item Type @{ML_type "int -> tactic"} represents tactics with
explicit subgoal addressing, with well-formedness conditions as
described above.
\item @{ML no_tac} is a tactic that always fails, returning the
empty sequence.
\item @{ML all_tac} is a tactic that always succeeds, returning a
singleton sequence with unchanged goal state.
\item @{ML print_tac}~@{text "message"} is like @{ML all_tac}, but
prints a message together with the goal state on the tracing
channel.
\item @{ML PRIMITIVE}~@{text rule} turns a primitive inference rule
into a tactic with unique result. Exception @{ML THM} is considered
a regular tactic failure and produces an empty result; other
exceptions are passed through.
\item @{ML SUBGOAL}~@{text "(fn (subgoal, i) => tactic)"} is the
most basic form to produce a tactic with subgoal addressing. The
given abstraction over the subgoal term and subgoal number allows to
peek at the relevant information of the full goal state. The
subgoal range is checked as required above.
\item @{ML CSUBGOAL} is similar to @{ML SUBGOAL}, but passes the
subgoal as @{ML_type cterm} instead of raw @{ML_type term}. This
avoids expensive re-certification in situations where the subgoal is
used directly for primitive inferences.
\end{description}
*}
subsection {* Resolution and assumption tactics \label{sec:resolve-assume-tac} *}
text {* \emph{Resolution} is the most basic mechanism for refining a
subgoal using a theorem as object-level rule.
\emph{Elim-resolution} is particularly suited for elimination rules:
it resolves with a rule, proves its first premise by assumption, and
finally deletes that assumption from any new subgoals.
\emph{Destruct-resolution} is like elim-resolution, but the given
destruction rules are first turned into canonical elimination
format. \emph{Forward-resolution} is like destruct-resolution, but
without deleting the selected assumption. The @{text "r/e/d/f"}
naming convention is maintained for several different kinds of
resolution rules and tactics.
Assumption tactics close a subgoal by unifying some of its premises
against its conclusion.
\medskip All the tactics in this section operate on a subgoal
designated by a positive integer. Other subgoals might be affected
indirectly, due to instantiation of schematic variables.
There are various sources of non-determinism, the tactic result
sequence enumerates all possibilities of the following choices (if
applicable):
\begin{enumerate}
\item selecting one of the rules given as argument to the tactic;
\item selecting a subgoal premise to eliminate, unifying it against
the first premise of the rule;
\item unifying the conclusion of the subgoal to the conclusion of
the rule.
\end{enumerate}
Recall that higher-order unification may produce multiple results
that are enumerated here.
*}
text %mlref {*
\begin{mldecls}
@{index_ML resolve_tac: "thm list -> int -> tactic"} \\
@{index_ML eresolve_tac: "thm list -> int -> tactic"} \\
@{index_ML dresolve_tac: "thm list -> int -> tactic"} \\
@{index_ML forward_tac: "thm list -> int -> tactic"} \\[1ex]
@{index_ML assume_tac: "int -> tactic"} \\
@{index_ML eq_assume_tac: "int -> tactic"} \\[1ex]
@{index_ML match_tac: "thm list -> int -> tactic"} \\
@{index_ML ematch_tac: "thm list -> int -> tactic"} \\
@{index_ML dmatch_tac: "thm list -> int -> tactic"} \\
\end{mldecls}
\begin{description}
\item @{ML resolve_tac}~@{text "thms i"} refines the goal state
using the given theorems, which should normally be introduction
rules. The tactic resolves a rule's conclusion with subgoal @{text
i}, replacing it by the corresponding versions of the rule's
premises.
\item @{ML eresolve_tac}~@{text "thms i"} performs elim-resolution
with the given theorems, which should normally be elimination rules.
\item @{ML dresolve_tac}~@{text "thms i"} performs
destruct-resolution with the given theorems, which should normally
be destruction rules. This replaces an assumption by the result of
applying one of the rules.
\item @{ML forward_tac} is like @{ML dresolve_tac} except that the
selected assumption is not deleted. It applies a rule to an
assumption, adding the result as a new assumption.
\item @{ML assume_tac}~@{text i} attempts to solve subgoal @{text i}
by assumption (modulo higher-order unification).
\item @{ML eq_assume_tac} is similar to @{ML assume_tac}, but checks
only for immediate @{text "\<alpha>"}-convertibility instead of using
unification. It succeeds (with a unique next state) if one of the
assumptions is equal to the subgoal's conclusion. Since it does not
instantiate variables, it cannot make other subgoals unprovable.
\item @{ML match_tac}, @{ML ematch_tac}, and @{ML dmatch_tac} are
similar to @{ML resolve_tac}, @{ML eresolve_tac}, and @{ML
dresolve_tac}, respectively, but do not instantiate schematic
variables in the goal state.
Flexible subgoals are not updated at will, but are left alone.
Strictly speaking, matching means to treat the unknowns in the goal
state as constants; these tactics merely discard unifiers that would
update the goal state.
\end{description}
*}
subsection {* Explicit instantiation within a subgoal context *}
text {* The main resolution tactics (\secref{sec:resolve-assume-tac})
use higher-order unification, which works well in many practical
situations despite its daunting theoretical properties.
Nonetheless, there are important problem classes where unguided
higher-order unification is not so useful. This typically involves
rules like universal elimination, existential introduction, or
equational substitution. Here the unification problem involves
fully flexible @{text "?P ?x"} schemes, which are hard to manage
without further hints.
By providing a (small) rigid term for @{text "?x"} explicitly, the
remaining unification problem is to assign a (large) term to @{text
"?P"}, according to the shape of the given subgoal. This is
sufficiently well-behaved in most practical situations.
\medskip Isabelle provides separate versions of the standard @{text
"r/e/d/f"} resolution tactics that allow to provide explicit
instantiations of unknowns of the given rule, wrt.\ terms that refer
to the implicit context of the selected subgoal.
An instantiation consists of a list of pairs of the form @{text
"(?x, t)"}, where @{text ?x} is a schematic variable occurring in
the given rule, and @{text t} is a term from the current proof
context, augmented by the local goal parameters of the selected
subgoal; cf.\ the @{text "focus"} operation described in
\secref{sec:variables}.
Entering the syntactic context of a subgoal is a brittle operation,
because its exact form is somewhat accidental, and the choice of
bound variable names depends on the presence of other local and
global names. Explicit renaming of subgoal parameters prior to
explicit instantiation might help to achieve a bit more robustness.
Type instantiations may be given as well, via pairs like @{text
"(?'a, \<tau>)"}. Type instantiations are distinguished from term
instantiations by the syntactic form of the schematic variable.
Types are instantiated before terms are. Since term instantiation
already performs simple type-inference, so explicit type
instantiations are seldom necessary.
*}
text %mlref {*
\begin{mldecls}
@{index_ML res_inst_tac: "Proof.context -> (indexname * string) list -> thm -> int -> tactic"} \\
@{index_ML eres_inst_tac: "Proof.context -> (indexname * string) list -> thm -> int -> tactic"} \\
@{index_ML dres_inst_tac: "Proof.context -> (indexname * string) list -> thm -> int -> tactic"} \\
@{index_ML forw_inst_tac: "Proof.context -> (indexname * string) list -> thm -> int -> tactic"} \\[1ex]
@{index_ML rename_tac: "string list -> int -> tactic"} \\
\end{mldecls}
\begin{description}
\item @{ML res_inst_tac}~@{text "ctxt insts thm i"} instantiates the
rule @{text thm} with the instantiations @{text insts}, as described
above, and then performs resolution on subgoal @{text i}.
\item @{ML eres_inst_tac} is like @{ML res_inst_tac}, but performs
elim-resolution.
\item @{ML dres_inst_tac} is like @{ML res_inst_tac}, but performs
destruct-resolution.
\item @{ML forw_inst_tac} is like @{ML dres_inst_tac} except that
the selected assumption is not deleted.
\item @{ML rename_tac}~@{text "names i"} renames the innermost
parameters of subgoal @{text i} according to the provided @{text
names} (which need to be distinct indentifiers).
\end{description}
For historical reasons, the above instantiation tactics take
unparsed string arguments, which makes them hard to use in general
ML code. The slightly more advanced @{ML Subgoal.FOCUS} combinator
of \secref{sec:struct-goals} allows to refer to internal goal
structure with explicit context management.
*}
section {* Tacticals \label{sec:tacticals} *}
text {* A \emph{tactical} is a functional combinator for building up
complex tactics from simpler ones. Common tacticals perform
sequential composition, disjunctive choice, iteration, or goal
addressing. Various search strategies may be expressed via
tacticals.
\medskip The chapter on tacticals in old \cite{isabelle-ref} is
still applicable for further details. *}
subsection {* Combining tactics *}
text {* Sequential composition and alternative choices are the most
basic ways to combine tactics, similarly to ``@{verbatim ","}'' and
``@{verbatim "|"}'' in Isar method notation. This corresponds to
@{ML_op "THEN"} and @{ML_op "ORELSE"} in ML, but there are further
possibilities for fine-tuning alternation of tactics such as @{ML_op
"APPEND"}. Further details become visible in ML due to explicit
subgoal addressing.
*}
text %mlref {*
\begin{mldecls}
@{index_ML_op "THEN": "tactic * tactic -> tactic"} \\
@{index_ML_op "ORELSE": "tactic * tactic -> tactic"} \\
@{index_ML_op "APPEND": "tactic * tactic -> tactic"} \\
@{index_ML "EVERY": "tactic list -> tactic"} \\
@{index_ML "FIRST": "tactic list -> tactic"} \\[0.5ex]
@{index_ML_op "THEN'": "('a -> tactic) * ('a -> tactic) -> 'a -> tactic"} \\
@{index_ML_op "ORELSE'": "('a -> tactic) * ('a -> tactic) -> 'a -> tactic"} \\
@{index_ML_op "APPEND'": "('a -> tactic) * ('a -> tactic) -> 'a -> tactic"} \\
@{index_ML "EVERY'": "('a -> tactic) list -> 'a -> tactic"} \\
@{index_ML "FIRST'": "('a -> tactic) list -> 'a -> tactic"} \\
@{index_ML "EVERY1": "(int -> tactic) list -> tactic"} \\
@{index_ML "FIRST1": "(int -> tactic) list -> tactic"} \\[0.5ex]
\end{mldecls}
\begin{description}
\item @{text "tac\<^sub>1"}~@{ML_op THEN}~@{text "tac\<^sub>2"} is the sequential
composition of @{text "tac\<^sub>1"} and @{text "tac\<^sub>2"}. Applied to a
proof state, it returns all states reachable in two steps by
applying @{text "tac\<^sub>1"} followed by @{text "tac\<^sub>2"}. First, it
applies @{text "tac\<^sub>1"} to the proof state, getting a sequence of
possible next states; then, it applies @{text "tac\<^sub>2"} to each of
these and concatenates the results to produce again one flat
sequence of states.
\item @{text "tac\<^sub>1"}~@{ML_op ORELSE}~@{text "tac\<^sub>2"} makes a choice
between @{text "tac\<^sub>1"} and @{text "tac\<^sub>2"}. Applied to a state, it
tries @{text "tac\<^sub>1"} and returns the result if non-empty; if @{text
"tac\<^sub>1"} fails then it uses @{text "tac\<^sub>2"}. This is a deterministic
choice: if @{text "tac\<^sub>1"} succeeds then @{text "tac\<^sub>2"} is excluded
from the result.
\item @{text "tac\<^sub>1"}~@{ML_op APPEND}~@{text "tac\<^sub>2"} concatenates the
possible results of @{text "tac\<^sub>1"} and @{text "tac\<^sub>2"}. Unlike
@{ML_op "ORELSE"} there is \emph{no commitment} to either tactic, so
@{ML_op "APPEND"} helps to avoid incompleteness during search, at
the cost of potential inefficiencies.
\item @{ML EVERY}~@{text "[tac\<^sub>1, \<dots>, tac\<^sub>n]"} abbreviates @{text
"tac\<^sub>1"}~@{ML_op THEN}~@{text "\<dots>"}~@{ML_op THEN}~@{text "tac\<^sub>n"}.
Note that @{ML "EVERY []"} is the same as @{ML all_tac}: it always
succeeds.
\item @{ML FIRST}~@{text "[tac\<^sub>1, \<dots>, tac\<^sub>n]"} abbreviates @{text
"tac\<^sub>1"}~@{ML_op ORELSE}~@{text "\<dots>"}~@{ML_op "ORELSE"}~@{text
"tac\<^sub>n"}. Note that @{ML "FIRST []"} is the same as @{ML no_tac}: it
always fails.
\item @{ML_op "THEN'"}, @{ML_op "ORELSE'"}, and @{ML_op "APPEND'"}
are lifted versions of @{ML_op "THEN"}, @{ML_op "ORELSE"}, and
@{ML_op "APPEND"}, for tactics with explicit subgoal addressing.
This means @{text "(tac\<^sub>1"}~@{ML_op THEN'}~@{text "tac\<^sub>2) i"} is the
same as @{text "(tac\<^sub>1 i"}~@{ML_op THEN}~@{text "tac\<^sub>2 i)"} etc.
\item @{ML "EVERY'"} and @{ML "FIRST'"} are lifted versions of @{ML
"EVERY'"} and @{ML "FIRST'"}, for tactics with explicit subgoal
addressing.
\item @{ML "EVERY1"} and @{ML "FIRST1"} are convenience versions of
@{ML "EVERY'"} and @{ML "FIRST'"}, applied to subgoal 1.
\end{description}
*}
subsection {* Repetition tacticals *}
text {* These tacticals provide further control over repetition of
tactics, beyond the stylized forms of ``@{verbatim "?"}'' and
``@{verbatim "+"}'' in Isar method expressions. *}
text %mlref {*
\begin{mldecls}
@{index_ML "TRY": "tactic -> tactic"} \\
@{index_ML "REPEAT_DETERM": "tactic -> tactic"} \\
@{index_ML "REPEAT_DETERM_N": "int -> tactic -> tactic"} \\
@{index_ML "REPEAT": "tactic -> tactic"} \\
@{index_ML "REPEAT1": "tactic -> tactic"} \\
@{index_ML "DETERM_UNTIL": "(thm -> bool) -> tactic -> tactic"} \\
\end{mldecls}
\begin{description}
\item @{ML TRY}~@{text "tac"} applies @{text "tac"} to the proof
state and returns the resulting sequence, if non-empty; otherwise it
returns the original state. Thus, it applies @{text "tac"} at most
once.
\item @{ML REPEAT_DETERM}~@{text "tac"} applies @{text "tac"} to the
proof state and, recursively, to the head of the resulting sequence.
It returns the first state to make @{text "tac"} fail. It is
deterministic, discarding alternative outcomes.
\item @{ML REPEAT_DETERM_N}~@{text "n tac"} is like @{ML
REPEAT_DETERM}~@{text "tac"} but the number of repetitions is bound
by @{text "n"} (where @{ML "~1"} means @{text "\<infinity>"}).
\item @{ML REPEAT}~@{text "tac"} applies @{text "tac"} to the proof
state and, recursively, to each element of the resulting sequence.
The resulting sequence consists of those states that make @{text
"tac"} fail. Thus, it applies @{text "tac"} as many times as
possible (including zero times), and allows backtracking over each
invocation of @{text "tac"}. @{ML REPEAT} is more general than @{ML
REPEAT_DETERM}, but requires more space.
\item @{ML REPEAT1}~@{text "tac"} is like @{ML REPEAT}~@{text "tac"}
but it always applies @{text "tac"} at least once, failing if this
is impossible.
\item @{ML DETERM_UNTIL}~@{text "P tac"} applies @{text "tac"} to
the proof state and, recursively, to the head of the resulting
sequence, until the predicate @{text "P"} (applied on the proof
state) yields @{ML true}. It fails if @{text "tac"} fails on any of
the intermediate states. It is deterministic, discarding alternative
outcomes.
\end{description}
*}
text %mlex {* The basic tactics and tacticals considered above follow
some algebraic laws:
\begin{itemize}
\item @{ML all_tac} is the identity element of the tactical @{ML_op
"THEN"}.
\item @{ML no_tac} is the identity element of @{ML_op "ORELSE"} and
@{ML_op "APPEND"}. Also, it is a zero element for @{ML_op "THEN"},
which means that @{text "tac"}~@{ML_op THEN}~@{ML no_tac} is
equivalent to @{ML no_tac}.
\item @{ML TRY} and @{ML REPEAT} can be expressed as (recursive)
functions over more basic combinators (ignoring some internal
implementation tricks):
\end{itemize}
*}
ML {*
fun TRY tac = tac ORELSE all_tac;
fun REPEAT tac st = ((tac THEN REPEAT tac) ORELSE all_tac) st;
*}
text {* If @{text "tac"} can return multiple outcomes then so can @{ML
REPEAT}~@{text "tac"}. @{ML REPEAT} uses @{ML_op "ORELSE"} and not
@{ML_op "APPEND"}, it applies @{text "tac"} as many times as
possible in each outcome.
\begin{warn}
Note the explicit abstraction over the proof state in the ML
definition of @{ML REPEAT}. Recursive tacticals must be coded in
this awkward fashion to avoid infinite recursion of eager functional
evaluation in Standard ML. The following attempt would make @{ML
REPEAT}~@{text "tac"} loop:
\end{warn}
*}
ML {*
(*BAD -- does not terminate!*)
fun REPEAT tac = (tac THEN REPEAT tac) ORELSE all_tac;
*}
subsection {* Scanning for a subgoal by number *}
text {* Tactics with explicit subgoal addressing
@{ML_type "int -> tactic"} can be used together with tacticals that
act like ``subgoal quantifiers'': guided by success of the body
tactic a certain range of subgoals is covered. Thus the body tactic
is applied to all subgoals, for example.
Suppose that the goal state has @{text "n \<ge> 0"} subgoals. Many of
these tacticals address subgoal ranges counting downwards from
@{text "n"} towards @{text "1"}. This has the fortunate effect that
newly emerging subgoals are concatenated in the result, without
interfering each other. Nonetheless, there might be situations
where a different order is desired, but it has to be achieved by
other means. *}
text %mlref {*
\begin{mldecls}
@{index_ML ALLGOALS: "(int -> tactic) -> tactic"} \\
@{index_ML TRYALL: "(int -> tactic) -> tactic"} \\
@{index_ML SOMEGOAL: "(int -> tactic) -> tactic"} \\
@{index_ML FIRSTGOAL: "(int -> tactic) -> tactic"} \\
@{index_ML REPEAT_SOME: "(int -> tactic) -> tactic"} \\
@{index_ML REPEAT_FIRST: "(int -> tactic) -> tactic"} \\
@{index_ML trace_goalno_tac: "(int -> tactic) -> int -> tactic"} \\
\end{mldecls}
\begin{description}
\item @{ML ALLGOALS}~@{text "tac"} is equivalent to @{text "tac
n"}~@{ML_op THEN}~@{text "\<dots>"}~@{ML_op THEN}~@{text "tac 1"}. It
applies the @{text tac} to all the subgoals, counting downwards.
\item @{ML TRYALL}~@{text "tac"} is equivalent to @{ML TRY}~@{text
"(tac n)"}~@{ML_op THEN}~@{text "\<dots>"}~@{ML_op THEN}~@{ML TRY}~@{text
"(tac 1)"}. It attempts to apply @{text "tac"} to all the subgoals.
\item @{ML SOMEGOAL}~@{text "tac"} is equivalent to @{text "tac
n"}~@{ML_op ORELSE}~@{text "\<dots>"}~@{ML_op ORELSE}~@{text "tac 1"}. It
applies @{text "tac"} to one subgoal, counting downwards.
\item @{ML FIRSTGOAL}~@{text "tac"} is equivalent to @{text "tac
1"}~@{ML_op ORELSE}~@{text "\<dots>"}~@{ML_op ORELSE}~@{text "tac n"}. It
applies @{text "tac"} to one subgoal, counting upwards.
\item @{ML REPEAT_SOME}~@{text "tac"} applies @{text "tac"} once or
more to a subgoal, counting downwards.
\item @{ML REPEAT_FIRST}~@{text "tac"} applies @{text "tac"} once or
more to a subgoal, counting upwards.
\item @{ML trace_goalno_tac}~@{text "tac i"} applies @{text "tac i"}
to the proof state. If the resulting sequence is non-empty, then it
is returned, with the side-effect of printing the selected subgoal.
Otherwise, it fails and prints nothing. It indicates that ``the
tactic worked for subgoal @{text "i"}'' and is mainly used with @{ML
SOMEGOAL} and @{ML FIRSTGOAL}.
\end{description}
*}
end