end
end
-redef class RapidTypeAnalysis
- redef fun add_type(mtype)
- do
- mtype.nlvt += 1
- mtype.mclass.nlvt += 1
- mtype.mclass.live_types.add(mtype)
- super(mtype)
- end
-
- redef fun add_cast_type(mtype)
- do
- mtype.nlct += 1
- mtype.mclass.nlct += 1
- mtype.mclass.cast_types.add(mtype)
- super(mtype)
- end
-end
redef class MType
- var nlvt: Int = 0
- var nlct: Int = 0
+ private var nlvt: Int = 0
+ private var nlct: Int = 0
- fun is_user_defined: Bool do
+ private fun is_standard: Bool do
var mtype = self
if mtype isa MNullableType then mtype = mtype.mtype
- return self.as(MClassType).mclass.is_user_defined
+ return self.as(MClassType).mclass.is_standard
end
- fun get_depth: Int do
+ private fun get_depth: Int do
var mtype = self
if mtype isa MNullableType then mtype = mtype.mtype
if not mtype isa MGenericType then return 0
end
redef class MClass
- var nlvt: Int = 0
- var nlct: Int = 0
- var live_types: Set[MType] = new HashSet[MType]
- var cast_types: Set[MType] = new HashSet[MType]
+ private var nlvt: Int = 0
+ private var nlct: Int = 0
+ private var live_types: Set[MType] = new HashSet[MType]
+ private var cast_types: Set[MType] = new HashSet[MType]
end
# Run a runtime type analysis and print metrics
for mtype in analysis.live_types do
mtypes.add(mtype)
nlvt += 1
+ mtype.mclass.nlvt += 1
+ mtype.mclass.live_types.add(mtype)
if mtype isa MGenericType then nlvtg += 1
- if mtype.is_user_defined then
+ if not mtype.is_standard then
nlvtudud += 1
if mtype isa MGenericType then nlvtgudud += 1
else
end
for mtype in analysis.live_cast_types do
+ if mtype isa MNullableType then mtype = mtype.mtype
+ if not mtype isa MClassType then continue
mtypes.add(mtype)
nlct += 1
+ mtype.mclass.nlct += 1
+ mtype.mclass.cast_types.add(mtype)
if mtype isa MGenericType then nlctg += 1
- if mtype.is_user_defined then
+ if not mtype.is_standard then
nlctudud += 1
if mtype isa MGenericType then nlctgudud += 1
else
end
# CSV generation
- if modelbuilder.toolcontext.opt_generate_csv.value then
- var summaryCSV = new CSVDocument(modelbuilder.toolcontext.output_dir.join_path("rta_sum_metrics.csv"))
+ if modelbuilder.toolcontext.opt_csv.value then
+ var summaryCSV = new CSVDocument
summaryCSV.set_header("scope", "NLVT", "NLVTG", "NLCT", "NLVCTG")
summaryCSV.add_line("global", nlvt, nlvtg, nlct, nlctg)
summaryCSV.add_line("SLUD", nlvtslud, nlvtgslud, nlctslud, nlctgslud)
summaryCSV.add_line("UDUD", nlvtudud, nlvtgudud, nlctudud, nlctgudud)
- summaryCSV.save
+ summaryCSV.save(modelbuilder.toolcontext.output_dir.join_path("rta_sum_metrics.csv"))
- var scalarCSV = new CSVDocument(modelbuilder.toolcontext.output_dir.join_path("rta_scalar_metrics.csv"))
- var udscalarCSV = new CSVDocument(modelbuilder.toolcontext.output_dir.join_path("rta_ud_scalar_metrics.csv"))
+ var scalarCSV = new CSVDocument
+ var udscalarCSV = new CSVDocument
scalarCSV.set_header("Type", "AGS", "DGS", "NLVT", "NLCT")
udscalarCSV.set_header("Type", "AGS", "DGS", "NLVT", "NLCT")
for mtype in mtypes do
var arity = 0
if mtype isa MGenericType then arity = mtype.arguments.length
- if mtype.is_user_defined then
+ if not mtype.is_standard then
udscalarCSV.add_line(mtype, arity, mtype.get_depth, mtype.nlvt, mtype.nlct)
end
scalarCSV.add_line(mtype, arity, mtype.get_depth, mtype.nlvt, mtype.nlct)
end
- scalarCSV.save
- udscalarCSV.save
+ scalarCSV.save(modelbuilder.toolcontext.output_dir.join_path("rta_scalar_metrics.csv"))
+ udscalarCSV.save(modelbuilder.toolcontext.output_dir.join_path("rta_ud_scalar_metrics.csv"))
- scalarCSV = new CSVDocument(modelbuilder.toolcontext.output_dir.join_path("rta_scalar_class_metrics.csv"))
- udscalarCSV = new CSVDocument(modelbuilder.toolcontext.output_dir.join_path("rta_ud_scalar_class_metrics.csv"))
+ scalarCSV = new CSVDocument
+ udscalarCSV = new CSVDocument
scalarCSV.set_header("Class", "AGS", "NLVV", "NLVT")
udscalarCSV.set_header("Class", "AGS", "NLVV", "inst")
for mclass in modelbuilder.model.mclasses do
if not mclass.is_class or mclass.is_abstract then continue
- if mclass.is_user_defined then
+ if not mclass.is_standard then
udscalarCSV.add_line(mclass.mclass_type, mclass.arity, mclass.live_types.length, mclass.nlvt)
end
scalarCSV.add_line(mclass.mclass_type, mclass.arity, mclass.live_types.length, mclass.nlvt)
end
- scalarCSV.save
- udscalarCSV.save
+ scalarCSV.save(modelbuilder.toolcontext.output_dir.join_path("rta_scalar_class_metrics.csv"))
+ udscalarCSV.save(modelbuilder.toolcontext.output_dir.join_path("rta_ud_scalar_class_metrics.csv"))
end
print "--- RTA metrics ---"
+ print "Number of live runtime classes: {analysis.live_classes.length}"
+ if analysis.live_classes.length < 8 then print "\t{analysis.live_classes.join(" ")}"
print "Number of live runtime types (instantied resolved type): {analysis.live_types.length}"
if analysis.live_types.length < 8 then print "\t{analysis.live_types.join(" ")}"
+ print "Number of live methods: {analysis.live_methods.length}"
+ if analysis.live_methods.length < 8 then print "\t{analysis.live_methods.join(" ")}"
print "Number of live method definitions: {analysis.live_methoddefs.length}"
if analysis.live_methoddefs.length < 8 then print "\t{analysis.live_methoddefs.join(" ")}"
- print "Number of live customized method definitions: {analysis.live_customized_methoddefs.length}"
- if analysis.live_customized_methoddefs.length < 8 then print "\t{analysis.live_customized_methoddefs.join(" ")}"
print "Number of live runtime cast types (ie used in as and isa): {analysis.live_cast_types.length}"
if analysis.live_cast_types.length < 8 then print "\t{analysis.live_cast_types.join(" ")}"
+
+ var x = 0
+ for p in analysis.live_methods do
+ for d in p.mpropdefs do
+ if analysis.live_methoddefs.has(d) or d.is_abstract then continue
+ x += 1
+ end
+ end
+ print "Number of dead method definitions of live methods: {x}"
end
nitlanguage / nit.git / blobdiff