Python PE.peToTuple方法代码示例

# 需要导入模块: import PE [as 别名]
# 或者: from PE import peToTuple [as 别名]
def insertAppend(C6, v, e) :
    """appends  e  to the end of array/list  v  in the heap.
       Does the same actions as an insertAssign to an indexed array,
       but preserves more heap info since the append does not produce
       any aliases within v

       params : C6; v - a vartee; e - an etree
    """
    sigma = C6["store"]
    heap = C6["heap"]
    vname = v[1]
    vold = Parse.makeOldVar(v)
    if lookupType(C6, vname) != "array" :
        error("cannot append to a non-list/array")
    else :
        loc = PE.peToTuple(sigma[vname])
        length = heap[loc][0]
        newlength = PE.add(length, PE.make(1))
        vector = heap[loc][1]

        # assign original to v_old:
        sigma[vold[1]] = sigma[vname]

        # make copy for the new value of  v:
        copy = {}
        for k in vector :
            copy[k] = vector[k]
        newloc = PE.make(PE.makeSym())
        rhs = PE.evall(C6, e)
        copy[ PE.peToTuple(length) ] = rhs
        sigma[vname] = newloc
        heap[ PE.peToTuple(newloc) ] = (newlength, copy)

# 需要导入模块: import PE [as 别名]
# 或者: from PE import peToTuple [as 别名]
def insertAssign(C6, v, etree):
    """updates the store of C6  with an assignment. 
       If v already exists in C6's store, saves former value as  v_old
       for later use in proof reasoning.

       params: v - has form,  ["var", s]  or  ["index", ["var", s], etree]
               etree - another etree, to be assigned to the var.
    """
    sigma = C6["store"]
    heap = C6["heap"]
    badvars = C6["novars"]
    if v[0] == "var" : vtree = v
    elif v[0] == "index" : vtree = v[1]
    vold = Parse.makeOldVar(vtree)  # ["var", vname_old]

    # first, check if we are allowed to update  v:
    if (vtree in badvars) :
        error("you may not update a protected global var outside of its maintenance function")
        return

    # if possible, rename current value of var v  as  v_old:

    if v[0] == "var" and v[1] in sigma : # and lookupType(C6, v[1]) != "array":
        sigma[vold[1]] = sigma[v[1]]  # assign v's current value to v_old
    elif v[0] == "index" and lookupType(C6, v[1][1]) == "array":
        vname = v[1][1]
        loc = PE.peToTuple(sigma[vname])
        length = heap[loc][0]
        vector = heap[loc][1]
        # make copy:
        copy = {}
        for k in vector :
            copy[k] = vector[k]
        # assign original to v_old and copy to v :
        sigma[vold[1]] = sigma[vname]
        newloc = PE.make(PE.makeSym())
        sigma[vname] = newloc
        heap[ PE.peToTuple(newloc) ] = (length, copy)

    # (later,  vold  will be erased from  sigma....)
    # now, eval assignment's  rhs  and store it into  v:
    rhs = PE.evall(C6, etree)

    if v[0] == "var":  # simple var
            sigma[v[1]] = rhs
    elif v[0] == "index":   # an array/list reference
        # eval  index  expression (NOTE: no nested indexing allowed):
        indexpe = PE.evall(C6, v[2])
        # save values in sigma[vname][1] provably distinct from  vname[index]:
        vname = v[1][1]
        if vname not in sigma or lookupType(C6, vname) != "array" :
            error(vname + " is not an array in the store")
            #sigma[vname] = PE.makeArray()
        else :
            vmap = heap[PE.peToTuple(sigma[vname])][1]
            saveDistinctElements(C6, vmap, indexpe)
            vmap[PE.peToTuple(indexpe)] = rhs

# 需要导入模块: import PE [as 别名]
# 或者: from PE import peToTuple [as 别名]
def reset(C6, modified_vars) :
    """changes  C6's sigma so that new constants are generated for
       each var mentioned in modified_vars.

       param: modified_vars, a sequence of lhs-trees; can be either
              ["var", s] or ["index" ["var", s] pe].   IMPORTANT:
              in the latter case, the  etree  has been replaced by its pe-value
    """
    sigma = C6["store"]
    heap = C6["heap"]
    #print "In reset"
    #print "store=", sigma
    for m in modified_vars :
        if m[0] == "var" and lookupType(C6, m[1]) != "array" :  # simple var
            sigma[m[1]] = PE.make(PE.makeSym())

        elif m[0] == "var" and lookupType(C6, m[1]) == "array" :
            arrayname = m[1]
            newarray = PE.makeArray()
            newloc = PE.make(PE.makeSym())
            sigma[m[1]] = newloc
            heap[PE.peToTuple(newloc)] = newarray

        elif m[0] == "index" or m[0] == "len" :
            vname = m[1][1]
            loc = PE.peToTuple(sigma[vname])
            length = heap[loc][0]
            vector = heap[loc][1]
            # make copy:
            copy = {}
            for k in vector :
                copy[k] = vector[k]
            newloc = PE.make(PE.makeSym())
            if m[0] == "index" : # indexed var ["index" ["var", s] pe]
                saveDistinctElements(C6, copy, PE.evall(C6, m[2]))
            elif m[0] == "len":  # ["len", ["var", s]], as a result of append
                length = PE.make(PE.makeSym())

            sigma[vname] = newloc
            heap[PE.peToTuple(newloc)] = (length, copy)

# 需要导入模块: import PE [as 别名]
# 或者: from PE import peToTuple [as 别名]
def copyWithoutStore(C6, funname, scalars, arrays, localglobals, brokeninvariants) :
    """makes a 2-deep copy of the functions, global invariants, novars
       within  C6. 
       Used to initialize a C6 for a function body for function,  funname

       Makes store and heap empty and places dummy scalar and array values
       in store based on  scalars  and  arrays .  Sets rels to []

       Subtracts  localglobals  from  ``novars'' list to denote that
                  these vars are mutable
       Revises  globalinvs list, removing brokeninvariants that are no longer
                  invariants because their vars are mutable
       Places  brokeninvariants  into  brokeninvs list

       params: C6;  
               funname : name of function
               scalars: vtree list of scalar vars;
               arrays: vtree list of array vars
               localglobals : vtree list of global vars that can be mutated
               brokeninvariants: invariants that mention
                      local globals, a btree list
       returns new C6 configuration
    """
    newC6 = empty()

    fcns = C6["funs"]
    for f in fcns :
        newC6["funs"][f] = fcns[f]

    newC6["globalinvs"] = [ g for g in C6["globalinvs"] \
                                       if g not in brokeninvariants ] 
    newC6["brokeninvs"] = brokeninvariants

    newC6["defs"] = [ d  for d in C6["defs"] ]
    newC6["novars"] = [ g for g in C6["novars"] if g not in localglobals]
    newC6["whoami"] = funname

    for v in scalars :
        newC6["store"][v[1]] = PE.make(PE.makeSym())
    for v in arrays :
        newloc = PE.make(PE.makeSym())
        newarray = PE.makeArray()
        newC6["store"][v[1]] = newloc
        newC6["heap"][PE.peToTuple(newloc)] = newarray

    return newC6

# 需要导入模块: import PE [as 别名]
# 或者: from PE import peToTuple [as 别名]
def lookupType(C6, vname):
    """looks inside C6's store to locate the data type of vname

       params: C6; vname - a string
       returns  "array" if  C6["store"][v] is a key linked to the heap
       returns  "int" if C6["store"][v] is not linked to the heap
       returns "unknown" if  v  not in store
    """
    sigma = C6["store"]
    if vname not in sigma :
        ans = "unknown"
    else :
        value = sigma[vname]
        if PE.peToTuple(value) in C6["heap"] :
            ans = "array"
        else :
            ans = "int"
    return ans