TY - GEN
T1 - Discounting in LTL
AU - Almagor, Shaull
AU - Boker, Udi
AU - Kupferman, Orna
PY - 2014
Y1 - 2014
N2 - In recent years, there is growing need and interest in formalizing and reasoning about the quality of software and hardware systems. As opposed to traditional verification, where one handles the question of whether a system satisfies, or not, a given specification, reasoning about quality addresses the question of how well the system satisfies the specification. One direction in this effort is to refine the "eventually" operators of temporal logic to discounting operators: the satisfaction value of a specification is a value in [0,1], where the longer it takes to fulfill eventuality requirements, the smaller the satisfaction value is. In this paper we introduce an augmentation by discounting of Linear Temporal Logic (LTL), and study it, as well as its combination with propositional quality operators. We show that one can augment LTL with an arbitrary set of discounting functions, while preserving the decidability of the model-checking problem. Further augmenting the logic with unary propositional quality operators preserves decidability, whereas adding an average-operator makes the model-checking problem undecidable. We also discuss the complexity of the problem, as well as various extensions.
AB - In recent years, there is growing need and interest in formalizing and reasoning about the quality of software and hardware systems. As opposed to traditional verification, where one handles the question of whether a system satisfies, or not, a given specification, reasoning about quality addresses the question of how well the system satisfies the specification. One direction in this effort is to refine the "eventually" operators of temporal logic to discounting operators: the satisfaction value of a specification is a value in [0,1], where the longer it takes to fulfill eventuality requirements, the smaller the satisfaction value is. In this paper we introduce an augmentation by discounting of Linear Temporal Logic (LTL), and study it, as well as its combination with propositional quality operators. We show that one can augment LTL with an arbitrary set of discounting functions, while preserving the decidability of the model-checking problem. Further augmenting the logic with unary propositional quality operators preserves decidability, whereas adding an average-operator makes the model-checking problem undecidable. We also discuss the complexity of the problem, as well as various extensions.
UR - http://www.scopus.com/inward/record.url?scp=84900540290&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-54862-8_37
DO - 10.1007/978-3-642-54862-8_37
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AN - SCOPUS:84900540290
SN - 9783642548611
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 424
EP - 439
BT - Tools and Algorithms for the Construction and Analysis of Systems - 20th Int. Conf., TACAS 2014, Held as Part of the European Joint Conf. on Theory and Practice of Software, ETAPS 2014, Proc.
PB - Springer Verlag
T2 - 20th International Conference on Tools and Algorithms for the Construction and Analysis of Systems, TACAS 2014 - Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2014
Y2 - 5 April 2014 through 13 April 2014
ER -