TY - GEN
T1 - Quantitative assume guarantee synthesis
AU - Almagor, Shaull
AU - Kupferman, Orna
AU - Ringert, Jan Oliver
AU - Velner, Yaron
N1 - Publisher Copyright: © Springer International Publishing AG 2017
PY - 2017
Y1 - 2017
N2 - In assume-guarantee synthesis, we are given a specification , describing an assumption on the environment and a guarantee for the system, and we construct a system that interacts with an environment and is guaranteed to satisfy G whenever the environment satisfies A. While assume-guarantee synthesis is 2EXPTIME-complete for specifications in LTL, researchers have identified the GR(1) fragment of LTL, which supports assume-guarantee reasoning and for which synthesis has an efficient symbolic solution. In recent years we see a transition to quantitative synthesis, in which the specification formalism is multi-valued and the goal is to generate high-quality systems, namely ones that maximize the satisfaction value of the specification. We study quantitative assume-guarantee synthesis. We start with specifications in LTL[F], an extension of LTL by quality operators. The satisfaction value of an LTL[F] formula is a real value in [0, 1], where the higher the value is, the higher is the quality in which the computation satisfies the specification. We define the quantitative extension GR(1)[F] of GR(1). We show that the implication relation, which is at the heart of assume-guarantee reasoning, has two natural semantics in the quantitative setting. Indeed, in addition to max{1 − A, G}, which is the multi-valued counterpart of Boolean implication, there are settings in which maximizing the ratio G/A is more appropriate. We show that GR(1)[F] formulas in both semantics are hard to synthesize. Still, in the implication semantics, we can reduce GR(1)[F] synthesis to GR(1) synthesis and apply its efficient symbolic algorithm. For the ratio semantics, we present a sound approximation, which can also be solved efficiently. Our experimental results show that our approach can successfully synthesize GR(1)[F] specifications with over a million of concrete states.
AB - In assume-guarantee synthesis, we are given a specification , describing an assumption on the environment and a guarantee for the system, and we construct a system that interacts with an environment and is guaranteed to satisfy G whenever the environment satisfies A. While assume-guarantee synthesis is 2EXPTIME-complete for specifications in LTL, researchers have identified the GR(1) fragment of LTL, which supports assume-guarantee reasoning and for which synthesis has an efficient symbolic solution. In recent years we see a transition to quantitative synthesis, in which the specification formalism is multi-valued and the goal is to generate high-quality systems, namely ones that maximize the satisfaction value of the specification. We study quantitative assume-guarantee synthesis. We start with specifications in LTL[F], an extension of LTL by quality operators. The satisfaction value of an LTL[F] formula is a real value in [0, 1], where the higher the value is, the higher is the quality in which the computation satisfies the specification. We define the quantitative extension GR(1)[F] of GR(1). We show that the implication relation, which is at the heart of assume-guarantee reasoning, has two natural semantics in the quantitative setting. Indeed, in addition to max{1 − A, G}, which is the multi-valued counterpart of Boolean implication, there are settings in which maximizing the ratio G/A is more appropriate. We show that GR(1)[F] formulas in both semantics are hard to synthesize. Still, in the implication semantics, we can reduce GR(1)[F] synthesis to GR(1) synthesis and apply its efficient symbolic algorithm. For the ratio semantics, we present a sound approximation, which can also be solved efficiently. Our experimental results show that our approach can successfully synthesize GR(1)[F] specifications with over a million of concrete states.
UR - http://www.scopus.com/inward/record.url?scp=85026765118&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-63390-9_19
DO - 10.1007/978-3-319-63390-9_19
M3 - منشور من مؤتمر
SN - 9783319633893
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 353
EP - 374
BT - Computer Aided Verification - 29th International Conference, CAV 2017, Proceedings
A2 - Kuncak, Viktor
A2 - Majumdar, Rupak
T2 - 29th International Conference on Computer Aided Verification, CAV 2017
Y2 - 24 July 2017 through 28 July 2017
ER -