details

property	value
status	complete
benchmark	rtL-cbn5.xml
ran by	Akihisa Yamada
cpu timeout	1200 seconds
wallclock timeout	300 seconds
memory limit	137438953472 bytes
execution host	n141.star.cs.uiowa.edu
space	Relative_05

run statistics

property	value
solver	AProVE
configuration	standard
runtime (wallclock)	5.26759 seconds
cpu usage	17.8155
user time	16.9112
system time	0.904299
max virtual memory	1.8701256E7
max residence set size	2604384.0

stage attributes

key	value
starexec-result	YES

output

YES proof of /export/starexec/sandbox2/benchmark/theBenchmark.xml # AProVE Commit ID: 794c25de1cacf0d048858bcd21c9a779e1221865 marcel 20200619 unpublished dirty Termination of the given RelTRS could be proven: (0) RelTRS (1) RelTRSSemanticLabellingPOLOProof [EQUIVALENT, 595 ms] (2) RelTRS (3) RelTRSSemanticLabellingPOLOProof [EQUIVALENT, 238 ms] (4) RelTRS (5) RelTRSRRRProof [EQUIVALENT, 0 ms] (6) RelTRS (7) RIsEmptyProof [EQUIVALENT, 0 ms] (8) YES ---------------------------------------- (0) Obligation: Relative term rewrite system: The relative TRS consists of the following R rules: top(ok(left(car(x, y), z))) -> top(check(right(y, z))) top(ok(right(x, car(y, z)))) -> top(check(left(x, z))) top(ok(left(bot, x))) -> top(check(right(bot, x))) top(ok(right(x, bot))) -> top(check(left(x, bot))) The relative TRS consists of the following S rules: top(ok(left(car(x, y), z))) -> top(check(left(y, z))) top(ok(right(x, car(y, z)))) -> top(check(right(x, z))) bot -> car(new, bot) check(old) -> ok(old) check(car(x, y)) -> car(check(x), y) check(car(x, y)) -> car(x, check(y)) check(left(x, y)) -> left(check(x), y) check(left(x, y)) -> left(x, check(y)) check(right(x, y)) -> right(check(x), y) check(right(x, y)) -> right(x, check(y)) car(ok(x), y) -> ok(car(x, y)) car(x, ok(y)) -> ok(car(x, y)) left(ok(x), y) -> ok(left(x, y)) left(x, ok(y)) -> ok(left(x, y)) right(ok(x), y) -> ok(right(x, y)) right(x, ok(y)) -> ok(right(x, y)) ---------------------------------------- (1) RelTRSSemanticLabellingPOLOProof (EQUIVALENT) We use Semantic Labelling over tuples of bools combined with a polynomial order [SEMLAB] We use semantic labelling over boolean tuples of size 1. We used the following model: top_1: component 1: OR[] ok_1: component 1: AND[] left_2: component 1: OR[x_1^1, x_2^1] car_2: component 1: OR[x_1^1, x_2^1] check_1: component 1: OR[x_1^1] right_2: component 1: OR[x_1^1, x_2^1] bot_0: component 1: OR[] new_0: component 1: OR[] old_0: component 1: AND[] Our labelling function was: top_1:component 1: XOR[x_1^1] ok_1:component 1: OR[] left_2:component 1: XOR[x_2^1] car_2:component 1: OR[x_2^1] check_1:component 1: XOR[] right_2:component 1: AND[x_1^1] bot_0:component 1: AND[] new_0:component 1: OR[] popout

output may be truncated. 'popout' for the full output.

job log

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actions

all output return to TRS Relative