Difference between pages "D32 Model Animation" and "Membership in Goal"

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= Model Animation =  
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= Objective =
  
== Overview ==
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This page describes the design of the reasoner MembershipGoal and its associated tactic MembershipGoalTac.<br>
=== Siemens Application===
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This reasoner discharges sequent whose goal denotes a membership which can be inferred from hypotheses. Here an basic example of what it discharges :<br>
The most important additions of the last 12 months are:
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<math>H,\quad x\in S,\quad S\subset T,\quad T\subseteq U \quad\vdash x\in U</math><br>
* Application of ProB in three active deployments, namely the upgrading of the Paris Metro Line 1 for driverless trains, line 4 of the S\~{a}o Paulo metro and line 9 of the Barcelona metro. We also briefly report on experiments on the models of the CDGVAL shuttle. The paper <ref>Leuschel et al. FM'2009</ref> only contained the initial San Juan case study, which was used to evaluate the potential of our approach.
+
The other purpose of the reasoner is to have a condense proof tree (one step contain several inference rule).
* In this article we describe the previous method adopted by Siemens in much more detail, as well as explaining the performance issues with Atelier B.
 
* Comparisons and empirical evaluations with other potential approaches and alternate tools (Brama, AnimB, BZ-TT and TLC) have been conducted.
 
* We provide more details about the ongoing validation process of ProB, which is required by Siemens for it to use ProB to replace the existing method.
 
  
The validation also lead to the discovery of errors in the English version of the Atelier B reference manual.
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= Analysis =
 
Also, since  <ref>Leuschel et al. FM'2009</ref>, ProB itself has been further improved inspired by the application, resulting in new optimisations in the kernel (see below).
 
  
More details:
+
Such sequent are proved by PP and ML. But, these provers have both drawbacks :
* <ref>Leuschel et al. FAC, special issue of FM'2009</ref>
+
*All the visible are added as needed hypotheses, which is most of the time not the case.
* <ref>Leuschel et al. Draft of Validation Report</ref>
+
*They take quite consequent time to prove it (even with the basic example given here above, the difference in time execution is noticeable).
 +
*If there are too many hypotheses, or if the expression of the <math>x</math> is too complicated, they may not prove it.
 +
This is particularly true when in the list of inclusion expressions of each side of the relation are not equal. For example : <math>H,\quad a\in S,\quad S\subset T_1\cap T_2,\quad T_1\cup T_3\subseteq  U\quad\vdash a\in U</math>
 +
<p>
 +
Such a reasoner contributes to prove more Proof Obligations automatically, faster and with fewer needed hypotheses which makes proof rule more legible and proof replay less sensitive to modifications.
  
=== Multi-level Animation ===
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= Design Decision =
(ABZ'2010 & SCP journal paper)
 
  
=== Improvements to the ProB Constraint solver and empirical evaluation ===
+
== Tactic ==
Various industrial applications have shown the need for improved constraint-solving capabilities (see CBC Deadlock, Test-Case Generation). In order to evaluate ProB, and detect areas for improvement, we have studied to what extent classical constraint satisfaction problems can be  conveniently expressed as B predicates, and then solved by ProB. In particular, we have studied problems such as the n-Queens problem, graph colouring, graph isomorphism detection, time tabling, Sudoku, Hanoi, magic squares, Alphametic puzzles, and several more. We have then compared the performance with respect to other tools, such as the model checker TLC  for TLA+, AnimB for Event-B,  and Alloy.
 
 
 
The experiments show that some constraint satisfaction problems can be expressed very conveniently in B and solved very effectively with ProB. For example, TLC takes 8747 seconds (2 hours 25 minuts) to solve the 9-queens problem expressed as a logical predicate; Alloy 4.1.10 with minisat takes 0.406 seconds, ProB 1.3.3 takes 0.01 seconds. For 32 queens, ProB 1.3.3 takes 0.28 seconds, while Alloy 4.1.10 with minisat takes over 4 minutes. For some others, the performance of ProB is still sub-optimal with respect to, e.g., Alloy; we plan to overcome this shortcoming in the future. Our long term goal is that B can not only be used to as a formal method for developing safety critical software, but also as a high-level constraint  programming language.
 
  
=== Constraint-Based Deadlock Checking ===
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This part explains how the tactic (MembershipGoalTac) associated to the reasoner MembershipGoal is working.
Ensuring the absence of deadlocks is important for certain applications, in particular for Bosch's Adaptive Cruise Control. We are tackling the problem of finding deadlocks via constraint solving rather than by model checking. Indeed, model checking is problematic when the out-degree is very large. In particular, quite often there can be a practically infinite number of ways to instantiate the constants of a B model. In this case, model checking will only find deadlocks for the given constants
+
=== Goal ===
chosen.
+
The tactic (as the reasoner) should works only on goals such as :
 +
*<math>\cdots~\in~\cdots</math>
 +
For examples :
 +
*<math>f(x)\in g\otimes h</math>
 +
*<math>x\in A\cprod\left(B\cup C\right)</math>
 +
*<math>x\mapsto y\in A\cprod B</math>
 +
In the latter case, the reasoner won't try to prove that ''x'' belongs to ''A'' and ''y'' belongs to ''B'', but that the mapplet belong to the Cartesian product.
 +
=== Hypotheses ===
 +
Now we have to find hypotheses leading to discharge the sequent. To do so, the tactic recovers two kinds of hypotheses :
 +
#the ones related to the left member of the goal <math>\left( x\in S\right)</math> (this is the start point):
 +
#*<math>x\in \cdots</math>
 +
#*<math>\cdots\mapsto x\mapsto\cdots\in\cdots</math>
 +
#*<math>\left\{\cdots, x,\cdots\right\}=/\subset/\subseteq\cdots</math>
 +
#*<math>\left\{\cdots, \cdots\mapsto x\mapsto\cdots,\cdots\right\}=/\subset/\subseteq\cdots</math>
 +
#*<math>f\ovl\left\{\cdots, x, \cdots\right\}=/\subset/\subseteq\cdots</math>
 +
#the ones denoting inclusion (all but the ones matching the description of the first point) :
 +
#*<math>\cdots\subset\cdots</math>
 +
#*<math>\cdots\subseteq\cdots</math>
 +
#*<math>\cdots=\cdots</math>
 +
Then, it will search a link between those hypotheses so that the sequent can be discharged.
  
Idea: solve constraints of axioms, invariant together with a constraint specifying a deadlock.
+
=== Find a path ===
 +
Now that we recovered all the hypotheses that could be useful for the reasoner, it remains to find a path among the hypotheses leading to discharge the sequent. Depending on the relations on each side of the inclusion, we will act differently. <math>f</math> always represent an expression (may be a domain, a range, etc.).
 +
#The following sequent is provable because <math>f\subseteq \varphi (f)</math>.
 +
#*<math>x\in f,\quad \varphi (f)\subseteq g\quad\vdash\quad x\in g</math>
 +
#*<math>\varphi (f) = f\quad\mid\quad f\cup h \quad\mid\quad h\cup f \quad\mid\quad h\ovl f</math>
 +
#The following sequent is provable because <math>\psi (f)\subseteq f</math>.
 +
#*<math>x\in \psi (f),\quad f\subseteq g\quad\vdash\quad x\in g</math>
 +
#*<math>\psi (f) = f\quad\mid\quad f\cap h \quad\mid\quad h\cap f \quad\mid\quad f\setminus h \quad\mid\quad f\ransub A \quad\mid\quad f\ranres A \quad\mid\quad A\domsub f \quad\mid\quad A\domres f</math>
 +
#We can generalized the first two points. This is the Russian dolls system. We can easily prove a sequent with multiple inclusions by going from hypothesis to hypothesis.
 +
#*<math>x\in \psi (f),\quad \varphi (f)\subseteq g\quad\vdash\quad x\in g</math>
 +
#For some relations, [[#positions|positions]] are needed to be known to continue to find hypotheses, but it is not always necessary.
 +
#*<math>x\mapsto y\in f,\quad f\subseteq A\cprod B\quad\vdash\quad x\in A</math>
 +
#*<math>x\in dom(f),\quad f\subseteq A\cprod B\quad\vdash\quad x\in A</math>
 +
#*<math>x\in ran(f),\quad f\subseteq A\cprod B\quad\vdash\quad x\in B</math>
  
Required Developments:
+
By using these inclusion and rewrites, it tries to find a path among the recovered hypotheses. Every one of those should only be used once, avoiding possible infinite loop <math>\left(A\subseteq B,\quad B\subseteq A\right)</math>. Among all paths that lead to discharge the sequent, the tactic give the first it finds. Moreover, so that the reasoner does not do the same work as the tactic of writing new hypothesis, it gives all needed hypotheses and added hypotheses in the input.
* implementation of the algorithm, with semantic relevance filtering (to be able to restrict the deadlock search to certain scenarios: in Bosch's case due to the flow plugin, one wants to restrict deadlock checking e.g. to states with the variable Counter set to 10).
 
* Improvements to ProB's constraint solving engine: (reification of constraints, more precise information propagation for membership constraints, performance improvments in the typchecker and other parts of the kernel)
 
  
Success: Model 1 and Model 2: CrCtrl_Comb2Final;
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== Reasoner ==
relevance of Counter=10 due to flow
 
  
Deadlock Freedom PO: 34 pages of ASCII, could not be loaded in Rodin "Java Heap Space Error". Counter examples found for 8 versions in 1-18 seconds.
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The way the reasoner must work is still in discussion.
  
=== BMotionStudio for Industrial Models ===
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= Implementation =  
  
Previously, we presented BMotion Studio, a visual editor which enables the developer of a formal model to set-up easily a domain specific visualization for discussing it with the domain expert. However, BMotion Studio had not yet reached the status of an Industrial strength tool due to the lack of important features known from modern editors.
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This section explain how the tactic has bee implemented.
  
In this work we present the improvements to BMotion Studio mainly aimed at upgrading it to an industrial strength tool and to show that we can apply the benefits of BMotion Studio for visualizing more complex models which are on the level of industrial applications. In order to reach this level the contribution of this work consists of three parts:
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=== Positions ===
 +
As it was said, we may sometimes need the position. It is represented by an array of integer. Here are the possible values the array contains (atomic positions) :
 +
* '''''kdom''''' : it corresponds to the domain.
 +
**<math>\left[A\cprod B\right]_{pos\;=\;kdom} = A</math>
 +
**<math>\left[x\mapsto y\right]_{pos\;=\;kdom} = x</math>
 +
**<math>\left[g\right]_{pos\;=\;kdom} = dom(g)</math>
 +
* '''''kran''''' : it corresponds to the domain.
 +
**<math>\left[A\cprod B\right]_{pos\;=\;kran} = B</math>
 +
**<math>\left[x\mapsto y\right]_{pos\;=\;kran} = y</math>
 +
**<math>\left[g\right]_{pos\;=\;kran} = ran(g)</math>
 +
* '''''converse''''' : it corresponds to the child of an inverse
 +
**<math>\left[f^{-1}\right]_{pos\;=\;converse}=f</math>
 +
**<math>\left[A\cprod B\right]_{pos\;=\;converse} = B\cprod A</math>
 +
For example, the following expressions at the given positions are equivalent.
 +
:<math>\left[ran(dom(g))\right]_{pos\;=\;\left[\right]} = \left[dom(g)\right]_{pos\;=\;\left[kran\right]} = \left[g\right]_{pos\;=\;\left[kdom,\; kran\right]}</math>
  
* We added a lot of new features to the graphical editor known from modern editors like: Copy-paste support, undo-redo support, rulers, guides and error reporting. One step towards was the redesign of the graphical editor with GEF.
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Some combinations of atomic positions are equivalent. In order to simplify comparison between positions, they are normalized :
* Since extensibility is a very important design principle for reaching the level of an industrial strength tool we pointed up the extensibility options of BMotion Studio.
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*<math>ran(f^{-1}) = dom(f)\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~kran\right]} = \left[f\right]_{pos\;=\;\left[kdom\right]}</math>
* We introduced the visualization for two models which are on the level of industrial applications in order to demonstrate that we can apply the benefits of BMotion Studio for visualizing more complex models. The first model is a mechanical press controller and the second model is a train system which manages the crossing of trains in a certain track network.
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*<math>dom(f^{-1}) = ran(f)\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~kdom\right]} = \left[f\right]_{pos\;=\;\left[kran\right]}</math>
 +
*<math>\left(f^{-1}\right)^{-1} = f\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~converse\right]} = \left[f\right]_{pos\;=\;\left[~\right]}</math>
  
=== Various other improvements ===
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=== Goal ===
  
mainly inspired by Siemens and Bosch Applications
+
As explained in the design decision part, goal is checked. If it matches the description here above <math>\left(x\in S\right)</math> then ''x'' is stored in an attribute. Moreover, from the set ''S'', we compute every pair ''expression'' & ''position'' equivalent to it. For example, from the set <math>dom(ran(ran(g)))</math>, the map will be computed :
 +
*<math>dom(ran(ran(g)))\;\mapsto\;[\;]</math>
 +
*<math>ran(ran(g))\;\mapsto\;[kdom]</math>
 +
*<math>ran(g)\;\mapsto\;[kran,~kdom]</math>
 +
*<math>g\;\mapsto\;[kran,~kran,~kdom]</math>
  
Improved AVL algorithms, more operators
+
A pair (expression ; position) is said equal to the goal if and only if there exists a pair equivalent to the goal (GoalExp ; GoalPos) and a pair equivalent to the given pair (Exp ; Pos) such as ''Pos = GoalPos'' and ''Exp'' is contained in ''GoalExp''.
  
record support, treatment of infinite sets,
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=== Hypotheses ===
  
== Motivations ==
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As explained in the design decision part, there are two kinds of hypotheses which are recovered. But when hypotheses related to the left member of the goal <math>\left(x\in S\right)</math> are stored, the position of ''x'' is also record. Then, if there is an hypothesis such as <math>\left\{\cdots\;,\;y\mapsto x\mapsto z\;,\;m\mapsto x\;,\;\cdots\right\} = A</math>, then this hypothesis is mapped to the positions <math>\left\{\left[0,~1\right],~\left[1\right]\right\}</math>.
  
The above works were motivated mainly to support the following three industrial deployments:
+
=== Find a path ===
* Siemens: enable Siemens to use ProB in their SIL4 development chain, replacing Atelier B for data validation.
 
* Bosch: provide animation and constraint-based deadlock detection for the Adaptive Cruise Control
 
* SAP: provide a way to generate test cases using constraint-based animation
 
  
== Available Documentation ==
+
Let's considered the sequent with the following goal : <math>x\in V</math>.
 +
We start with the hypotheses which have a connection with the goal's member. Such a hypothesis gives two informations : the position <math>pos</math> and the set <math>S</math> as explained in [[#Hypotheses|hypotheses]]. Then, for each equivalent pair to these one <math>\left(S', pos'\right)</math>, we compute set containing <math>S'</math> ([[#Design Decision#Tactic#Find a path| Find a path 2.]]). For every new pair, we test if it is contained in the goal.
  
=== References ===
+
To be continued.
<references/>
 
  
== Planning ==
+
= Untreated cases =
  
* Finish Validation Report
+
Some cases are not treated. Further enhancement may be provided for some.
* Write up Constraint-Based Deadlock Checking and integrate fully into Rodin Platform
+
*<math>x\in f,\quad f\in A\;op\;B\quad\vdash\quad x\in A\cprod B</math>
* Support mathematical extensions in ProB
+
*<math>x\in f\otimes g,\quad f\subseteq A\cprod B,\quad g\subseteq C\cprod D\quad\vdash\quad x\in (A\cprod C)\cprod(B\cprod D)</math>
* Further improvements in the constraint-solving kernel of ProB; in particular for relations and operators. A Kodkod translator is being developed.
+
*<math>x\in f\otimes g,\quad f\subseteq h\quad\vdash\quad x\in h\otimes g</math>
 +
*<math>x\in \left\{a,~b,~c\right\},\quad\left\{a,~b,~c,~d,~e,~f\right\}\subseteq D\quad\vdash\quad x\in D</math>
 +
*<math>x\in A\cprod B,\quad A\subseteq C\quad\vdash\quad x\in C\cprod B</math>
 +
*<math>x\in dom(f)\cap A\quad\vdash\quad x\in dom(A\domres f)</math>
 +
*<math>x\in ran(f)\cap A\quad\vdash\quad x\in ran(f\ranres A)</math>
 +
*<math>x\in dom(A\domres f)\quad\vdash\quad x\in dom(f)\cap A</math>
 +
*<math>x\in ran(f\ranres A)\quad\vdash\quad x\in ran(f)\cap A</math>
 +
*<math>x\in \quad\vdash\quad</math>
 +
*<math>\quad\vdash\quad</math>
 +
*<math>\quad\vdash\quad</math>
 +
*<math>\quad\vdash\quad</math>
 +
*:<math>\bigl(</math> where <math>op_1</math> and <math>op_2</math> are ones of :<math>\quad\rel, \trel, \srel, \strel, \pfun, \tfun, \pinj, \tinj, \psur, \tsur, \tbij\bigr)</math>
 +
 
 +
[[Category:Design proposal]]

Revision as of 10:03, 10 August 2011

Objective

This page describes the design of the reasoner MembershipGoal and its associated tactic MembershipGoalTac.
This reasoner discharges sequent whose goal denotes a membership which can be inferred from hypotheses. Here an basic example of what it discharges :
H,\quad x\in S,\quad S\subset T,\quad T\subseteq U \quad\vdash x\in U
The other purpose of the reasoner is to have a condense proof tree (one step contain several inference rule).

Analysis

Such sequent are proved by PP and ML. But, these provers have both drawbacks :

  • All the visible are added as needed hypotheses, which is most of the time not the case.
  • They take quite consequent time to prove it (even with the basic example given here above, the difference in time execution is noticeable).
  • If there are too many hypotheses, or if the expression of the x is too complicated, they may not prove it.

This is particularly true when in the list of inclusion expressions of each side of the relation are not equal. For example : H,\quad a\in S,\quad S\subset T_1\cap T_2,\quad T_1\cup T_3\subseteq  U\quad\vdash a\in U

Such a reasoner contributes to prove more Proof Obligations automatically, faster and with fewer needed hypotheses which makes proof rule more legible and proof replay less sensitive to modifications.

Design Decision

Tactic

This part explains how the tactic (MembershipGoalTac) associated to the reasoner MembershipGoal is working.

Goal

The tactic (as the reasoner) should works only on goals such as :

  • \cdots~\in~\cdots

For examples :

  • f(x)\in g\otimes h
  • x\in A\cprod\left(B\cup C\right)
  • x\mapsto y\in A\cprod B

In the latter case, the reasoner won't try to prove that x belongs to A and y belongs to B, but that the mapplet belong to the Cartesian product.

Hypotheses

Now we have to find hypotheses leading to discharge the sequent. To do so, the tactic recovers two kinds of hypotheses :

  1. the ones related to the left member of the goal \left( x\in S\right) (this is the start point):
    • x\in \cdots
    • \cdots\mapsto x\mapsto\cdots\in\cdots
    • \left\{\cdots, x,\cdots\right\}=/\subset/\subseteq\cdots
    • \left\{\cdots, \cdots\mapsto x\mapsto\cdots,\cdots\right\}=/\subset/\subseteq\cdots
    • f\ovl\left\{\cdots, x, \cdots\right\}=/\subset/\subseteq\cdots
  2. the ones denoting inclusion (all but the ones matching the description of the first point) :
    • \cdots\subset\cdots
    • \cdots\subseteq\cdots
    • \cdots=\cdots

Then, it will search a link between those hypotheses so that the sequent can be discharged.

Find a path

Now that we recovered all the hypotheses that could be useful for the reasoner, it remains to find a path among the hypotheses leading to discharge the sequent. Depending on the relations on each side of the inclusion, we will act differently. f always represent an expression (may be a domain, a range, etc.).

  1. The following sequent is provable because f\subseteq \varphi (f).
    • x\in f,\quad \varphi (f)\subseteq g\quad\vdash\quad x\in g
    • \varphi (f) = f\quad\mid\quad f\cup h \quad\mid\quad h\cup f \quad\mid\quad h\ovl f
  2. The following sequent is provable because \psi (f)\subseteq f.
    • x\in \psi (f),\quad f\subseteq g\quad\vdash\quad x\in g
    • \psi (f) = f\quad\mid\quad f\cap h \quad\mid\quad h\cap f \quad\mid\quad f\setminus h \quad\mid\quad f\ransub A \quad\mid\quad f\ranres A \quad\mid\quad A\domsub f \quad\mid\quad A\domres f
  3. We can generalized the first two points. This is the Russian dolls system. We can easily prove a sequent with multiple inclusions by going from hypothesis to hypothesis.
    • x\in \psi (f),\quad \varphi (f)\subseteq g\quad\vdash\quad x\in g
  4. For some relations, positions are needed to be known to continue to find hypotheses, but it is not always necessary.
    • x\mapsto y\in f,\quad f\subseteq A\cprod B\quad\vdash\quad x\in A
    • x\in dom(f),\quad f\subseteq A\cprod B\quad\vdash\quad x\in A
    • x\in ran(f),\quad f\subseteq A\cprod B\quad\vdash\quad x\in B

By using these inclusion and rewrites, it tries to find a path among the recovered hypotheses. Every one of those should only be used once, avoiding possible infinite loop \left(A\subseteq B,\quad B\subseteq A\right). Among all paths that lead to discharge the sequent, the tactic give the first it finds. Moreover, so that the reasoner does not do the same work as the tactic of writing new hypothesis, it gives all needed hypotheses and added hypotheses in the input.

Reasoner

The way the reasoner must work is still in discussion.

Implementation

This section explain how the tactic has bee implemented.

Positions

As it was said, we may sometimes need the position. It is represented by an array of integer. Here are the possible values the array contains (atomic positions) :

  • kdom : it corresponds to the domain.
    • \left[A\cprod B\right]_{pos\;=\;kdom} = A
    • \left[x\mapsto y\right]_{pos\;=\;kdom} = x
    • \left[g\right]_{pos\;=\;kdom} = dom(g)
  • kran : it corresponds to the domain.
    • \left[A\cprod B\right]_{pos\;=\;kran} = B
    • \left[x\mapsto y\right]_{pos\;=\;kran} = y
    • \left[g\right]_{pos\;=\;kran} = ran(g)
  • converse : it corresponds to the child of an inverse
    • \left[f^{-1}\right]_{pos\;=\;converse}=f
    • \left[A\cprod B\right]_{pos\;=\;converse} = B\cprod A

For example, the following expressions at the given positions are equivalent.

\left[ran(dom(g))\right]_{pos\;=\;\left[\right]} = \left[dom(g)\right]_{pos\;=\;\left[kran\right]} = \left[g\right]_{pos\;=\;\left[kdom,\; kran\right]}

Some combinations of atomic positions are equivalent. In order to simplify comparison between positions, they are normalized :

  • ran(f^{-1}) = dom(f)\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~kran\right]} = \left[f\right]_{pos\;=\;\left[kdom\right]}
  • dom(f^{-1}) = ran(f)\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~kdom\right]} = \left[f\right]_{pos\;=\;\left[kran\right]}
  • \left(f^{-1}\right)^{-1} = f\quad\limp\quad \left[f\right]_{pos \;=\; \left[converse,~converse\right]} = \left[f\right]_{pos\;=\;\left[~\right]}

Goal

As explained in the design decision part, goal is checked. If it matches the description here above \left(x\in S\right) then x is stored in an attribute. Moreover, from the set S, we compute every pair expression & position equivalent to it. For example, from the set dom(ran(ran(g))), the map will be computed :

  • dom(ran(ran(g)))\;\mapsto\;[\;]
  • ran(ran(g))\;\mapsto\;[kdom]
  • ran(g)\;\mapsto\;[kran,~kdom]
  • g\;\mapsto\;[kran,~kran,~kdom]

A pair (expression ; position) is said equal to the goal if and only if there exists a pair equivalent to the goal (GoalExp ; GoalPos) and a pair equivalent to the given pair (Exp ; Pos) such as Pos = GoalPos and Exp is contained in GoalExp.

Hypotheses

As explained in the design decision part, there are two kinds of hypotheses which are recovered. But when hypotheses related to the left member of the goal \left(x\in S\right) are stored, the position of x is also record. Then, if there is an hypothesis such as \left\{\cdots\;,\;y\mapsto x\mapsto z\;,\;m\mapsto x\;,\;\cdots\right\} = A, then this hypothesis is mapped to the positions \left\{\left[0,~1\right],~\left[1\right]\right\}.

Find a path

Let's considered the sequent with the following goal : x\in V. We start with the hypotheses which have a connection with the goal's member. Such a hypothesis gives two informations : the position pos and the set S as explained in hypotheses. Then, for each equivalent pair to these one \left(S', pos'\right), we compute set containing S' ( Find a path 2.). For every new pair, we test if it is contained in the goal.

To be continued.

Untreated cases

Some cases are not treated. Further enhancement may be provided for some.

  • x\in f,\quad f\in A\;op\;B\quad\vdash\quad x\in A\cprod B
  • x\in f\otimes g,\quad f\subseteq A\cprod B,\quad g\subseteq C\cprod D\quad\vdash\quad x\in (A\cprod C)\cprod(B\cprod D)
  • x\in f\otimes g,\quad f\subseteq h\quad\vdash\quad x\in h\otimes g
  • x\in \left\{a,~b,~c\right\},\quad\left\{a,~b,~c,~d,~e,~f\right\}\subseteq D\quad\vdash\quad x\in D
  • x\in A\cprod B,\quad A\subseteq C\quad\vdash\quad x\in C\cprod B
  • x\in dom(f)\cap A\quad\vdash\quad x\in dom(A\domres f)
  • x\in ran(f)\cap A\quad\vdash\quad x\in ran(f\ranres A)
  • x\in dom(A\domres f)\quad\vdash\quad x\in dom(f)\cap A
  • x\in ran(f\ranres A)\quad\vdash\quad x\in ran(f)\cap A
  • x\in \quad\vdash\quad
  • \quad\vdash\quad
  • \quad\vdash\quad
  • \quad\vdash\quad
    \bigl( where op_1 and op_2 are ones of :\quad\rel, \trel, \srel, \strel, \pfun, \tfun, \pinj, \tinj, \psur, \tsur, \tbij\bigr)