Monitoring Business Metaconstraints Based on LTL & LDL for - PowerPoint PPT Presentation

Monitoring Business Metaconstraints Based on LTL & LDL for Finite Traces Marco Montali KRDB Research Centre for Knowledge and Data Free University of Bozen-Bolzano Joint work with: G. De Giacomo, R. De Masellis, M. Grasso, F.M. Maggi BPM 2014 Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 1 / 26

Process Mining Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 2 / 26

Process Mining Classicaly applied to post-mortem data. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 3 / 26

Operational Decision Support Extension of classical process mining to current, live data. people “world” organizations business machines processes documents information system(s) provenance event logs “pre “post current historic mortem” mortem” data data cartography navigation auditing recommend compare discover enhance diagnose explore promote predict detect check models de jure models de facto models control-flow control-flow data/rules data/rules resources/ resources/ organization organization Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 4 / 26

Detecting Deviations Auditing: find deviations between observed and expected behaviors. event logs “pre “post The current historic mortem” mortem” data data auditing compare promote detect check o he models de jure models de facto models ee control-flow control-flow data/rules data/rules resources/ resources/ organization organization l. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 5 / 26

Detecting Deviations Auditing: find deviations between observed and expected behaviors. event logs “pre “post The current historic mortem” mortem” Our setting: data data Model auditing Declarative business constraints. compare promote detect check o • E.g., Declare . he Monitoring models de jure models de facto models • Online, evolving observations. ee control-flow control-flow • Prompt deviation detection. data/rules data/rules resources/ resources/ organization organization l. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 5 / 26

On Promptness Flight routes (thanks Claudio!) • When the airplane takes off, it must eventually reach the destination airport. • When the airplane is re-routed, it cannot reach the destination airport anymore. • If a dangerous situation is detected at the destination, airplane must be re-routed. danger take-off reach re-route Question Consider trace: danger take-off Is there any deviation? Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 6 / 26

Boring Answer: Apparently Not Reactive Monitor • Checks the partial trace observed so far. • Suspends the judgment if no conclusive answer can be given. re-route danger take-off reach danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 7 / 26

Boring Answer: Apparently Not Reactive Monitor • Checks the partial trace observed so far. • Suspends the judgment if no conclusive answer can be given. re-route danger take-off reach danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 7 / 26

Prophetic Answer: YES Proactive Monitor • Checks the partial trace observed so far. • Looks into the future(s). danger take-off reach re-route danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 8 / 26

Prophetic Answer: YES Proactive Monitor • Checks the partial trace observed so far. • Looks into the future(s). danger take-off reach re-route danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 8 / 26

Prophetic Answer: YES Proactive Monitor • Checks the partial trace observed so far. • Looks into the future(s). danger take-off reach re-route danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 8 / 26

Prophetic Answer: YES Proactive Monitor • Checks the partial trace observed so far. • Looks into the future(s). ✷ ( take-off → ✸ reach ) ∧ ¬ ( ✸ ( reach ) ∧ ✸ ( re-route )) ∧ ✷ ( danger → ✸ re-route ) danger take-off Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 8 / 26

Logics on Finite Traces Goal Reasoning on finite partial traces and their finite suffixes. Typical Solution: ltl f Adopt LTL on finite traces and corresponding techniques based on Finite-State Automata. a a Not Büchi automata! Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 9 / 26

Logics on Finite Traces Goal Reasoning on finite partial traces and their finite suffixes. Typical Solution: ltl f Adopt LTL on finite traces and corresponding techniques based on Finite-State Automata. a a Not Büchi automata! Huge difference, often neglected, between LTL on finite and infinite traces! See [AAAI2014] Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 9 / 26

Problem #1: Monitoring Proactive monitoring requires to refine the standard ltl f semantics. RV-LTL Given an LTL formula ϕ : • [ ϕ ] RV = true ❀ OK; • [ ϕ ] RV = false ❀ BAD; • [ ϕ ] RV = temp _ true ❀ OK now, could become BAD in the future; • [ ϕ ] RV = temp _ false ❀ BAD now, could become OK in the future. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 10 / 26

Problem #1: Monitoring Proactive monitoring requires to refine the standard ltl f semantics. RV-LTL Given an LTL formula ϕ : • [ ϕ ] RV = true ❀ OK; • [ ϕ ] RV = false ❀ BAD; • [ ϕ ] RV = temp _ true ❀ OK now, could become BAD in the future; • [ ϕ ] RV = temp _ false ❀ BAD now, could become OK in the future. However. . . • Typically studied on infinite traces: detour to Büchi automata. • Only ad-hoc techniques on finite traces [BPM2011]. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 10 / 26

Problem #2: Contextual Business Constraints Need for monitoring constraints only when specific circumstances hold. • Compensation constraints. • Contrary-do-duty expectations. • . . . Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 11 / 26

Problem #2: Contextual Business Constraints Need for monitoring constraints only when specific circumstances hold. • Compensation constraints. • Contrary-do-duty expectations. • . . . However. . . • Cannot be systematically captured at the level of constraint specification. Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 11 / 26

Suitability of the Constraint Specification Language Star-free FOL over ltl f regular finite traces expressions Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 12 / 26

Suitability of the Constraint Specification Language MSOL over Regular finite traces expressions Star-free FOL over ltl f regular finite traces expressions Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 12 / 26

Suitability of the Constraint Specification Language MSOL over Regular finite traces expressions pspace complexity Nondet. Star-free finite-state FOL over ltl f regular automata finite traces expressions ( nfa ) • ltl f : declarative, but lacking expressiveness. • Regular expressions: rich formalism, but low-level. � (( r | other ) ∗ ( t ( t | other ) ∗ r )( r | other ) ∗ ) ∗ (t)ake-off (r)each Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 12 / 26

Suitability of the Constraint Specification Language ldl f MSOL over Regular Linear Dynamic finite traces expressions pspace Logic over complexity finite traces Nondet. Star-free finite-state FOL over ltl f regular automata finite traces expressions ( nfa ) • ltl f : declarative, but lacking expressiveness. • Regular expressions: rich formalism, but low-level. � (( r | other ) ∗ ( t ( t | other ) ∗ r )( r | other ) ∗ ) ∗ (t)ake-off (r)each • ldl f : combines the best of the two! Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 12 / 26

The Logic ldl f [De Giacomo&Vardi,IJCAI13] Merges ltl f with regular expressions, through the syntax of Propositional Dynamic Logic (PDL): ϕ ::= φ | tt | ff | ¬ ϕ | ϕ 1 ∧ ϕ 2 | � ρ � ϕ | [ ρ ] ϕ φ | ϕ ? | ρ 1 + ρ 2 | ρ 1 ; ρ 2 | ρ ∗ ρ ::= ϕ : ltl f part; ρ : regular expression part. They mutually refer to each other: • � ρ � ϕ states that, from the current step in the trace, there is an execution satisfying ρ such that its last step satisfies ϕ . • [ ρ ] ϕ states that, from the current step in the trace, all execution satisfying ρ are such that their last step satisfies ϕ . • ϕ ? checks whether ϕ is true in the current step and, if so, continues to evaluate the remaining execution. Of special interest is end = [ true ?] ff , to check whether the trace has been completed (the remaining trace is the empty one). Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 13 / 26

Runtime ldl f Monitors Check partial trace π = e 1 , . . . , e n against formula ϕ . From ad-hoc techniques . . .  temp _ true  � �  | temp _ false   . . . e 1 e n ϕ = RV = true    false  Marco Montali (unibz) Monitoring Business Metaconstraints BPM 2014 14 / 26