Benefits of Interval Temporal Logic for Specification of Concurrent Systems

Transcription

1 Benefits of Interval Temporal Logic for Specification of Concurrent Systems Ben Moszkowski Software Technology Research Laboratory De Montfort University Leicester Great Britain Cambridge Concurrency Workshop July 10 1

2 Introduction Intervals and discrete linear state sequences offer a compellingly natural and flexible way to model computational processes involving hardware or software. Finite or infinite state sequence: Interval Temporal Logic (ITL) is an established formalism (over 25 years old) for reasoning about such phenomena. It includes operators for sequentially combining formulas. For example, if A and B are formulas, so are following A; B ( chop ) A ( chop-star ). ITL can express various imperative programming constructs (e.g., while-loops) and has executable subsets. The Duration Calculus (DC) is a real-time extension of ITL for hybrid systems. 2

3 ITL, Point-Based Temporal Logic and Time Reversal For several decades, widely held conventional wisdom: Point-based linear-time temporal logic (e.g., PTL) is much superior to ITL for safety and liveness concurrency properties. ITL s computational intractability seen as limit to tool support. We offer evidence suggesting that a reexamination is in order. Our presentation uses Peterson s mutual exclusion algorithm. Interval properties can be more natural and at higher level than point-based ones. Use transformations with time reversal and from infinite time to finite time. For tool support, transform to lower-level, point-based formulas. Hence point-based linear-time temporal logic primarily serves as a subordinate formalism. 3

4 4 Syntax of Propositional ITL In what follows, p is any propositional variable and both A and B themselves denote formulas in Propositional ITL (PITL): true p A A B skip A; B A. ; is called chop. is called chop-star.

5 5 Intervals of Time Discrete linear time is represented by intervals (i.e., sequences of states). An interval σ has a finite, nonzero number of states σ 0, σ 1,.... Can naturally extend to also permit infinite (i.e., ω) states. Each state σ i maps each variable p, q,... to true or false. The value of p in the state σ i is denoted σ i (p). Hence, propositional variables p, q,... are local to states.

6 Semantics of PITL for Finite Time Let σ = A denote that the interval σ satisfies the PITL formula A. Below is excerpt from semantics of basic PITL constructs: σ = p iff σ 0 (p) = true. (Use p s value in σ s initial state σ 0 ) σ = A iff σ = A. σ = A B iff σ = A or σ = B. Pictorial summary of finite-time semantics of interval constructs: skip A B A A B A Each pair of adjacent subintervals share a state. Can also have chomp, a version of chop with unit gap: A; skip; B. A A 6

7 7 Some Sample Formulas (Assume Finite Time) p p: t f f p skip p: t f skip; p ( p) p: f t t f skip p true; p ( p) p: f t t f t f true p (true; p) ( p) p: t t t t t t

8 8 Notes A, A, B, C,... denote arbitrary formulas. w, w,... denote state formulas (no temporal operators). If σ = A for some σ, then A is satisfiable. If σ = A for all σ, then A is valid. Denote as = A. Can extend PITL to include infinite time and A ω (chop-omega).

9 9 Some Derivable ITL Operators Define false, A B, A B (implies), A B (equivalence),.... Propositional Temporal Logic (PTL) with finite & infinite time: def A skip; A ( next ) more finite A def true ( 2 states) empty def more def empty (finite) inf def finite (just 1 state) (infinite) def finite; A ( eventually ) A def A ( henceforth ) fin A def (empty A) (final state) A B def finite ( (fin A) B ) (temporal assignment) Interval-oriented operators: f f A ω A def (A finite); true (Some finite prefix) A def f A (ALL finite prefixes) def (A finite) inf (Chop-omega)

10 Sequential Compositionality with Temporal Fixpoints ITL-based assumptions and commitments for a system Sys: w As Sys Co fin w Sequential composition of two formulas Sys and Sys : = w As Sys Co fin w = w As Sys Co fin w = w As (Sys; Sys ) Co fin w Zero or more iterations of a formula Sys: = w As Sys Co fin w = w As Sys Co fin w See Moszkowski 94 (also 96, 98) (Shares some features with Jones rely/guarantee conditions) 10

11 Commitments as Fixpoints Formalization: = Co Co Intuition: Co is true on an interval iff Co is true on each of a sequence of subintervals. Examples: p s values in the initial and final states are equal (p p) p: f t t f f t t f p p p p p p Any formula A Example: even length (skip; skip) Any formula expressible as (more f B). Examples: (more w), ( (more w) w ) 11

12 Peterson s Mutual Exclusion Algorithm Process P 0 : do forever (... Noncritical section... ) flag 0 := 1; turn := 0; await(flag 1 = 0 turn = 1); cs 0 := 1; (... Critical section... ) cs 0 := 0; flag 0 := 0; (... Noncritical section... ) Overall program has two processes P 0 and P 1 : flag 0 = flag 1 = cs 0 = cs 1 = 0 turn = 0 (P 0 P 1 ) See textbook Synchronization Algorithms and Concurrent Programming, G. Taubenfeld (Pearson/Prentice Hall, 2006). 12

13 Safety Property Can express behaviour of the program in PITL. Recall that f A means: A is true in all finite prefix subintervals. Safety property for mutual exclusion expressible as f (more B). ( Includes formulas of form f (more fin w) C ). Safety property for individual process in Peterson s algorithm: ( f (more fin(cs 0 = 1)) (test; stability; test; stability) ). Star-free operand of f reducible to point-based temporal logic. Can use f instead of past-time constructs. 13

14 Time Reversal and Chop-Star Fixpoints Let σ r denote temporal reverse of finite interval σ: σ σ... σ 0. Let A r be like A in reverse: σ r = A iff σ = A r for finite intervals. Sample finite-time semantic equivalences: (A B) r A r B r (A;B) r B r ;A r more r more ( f A) r (A r ). For finite time: = finite A iff = finite A r. Time reversal of f (more B) with finite time: ( f (more B) ) r (more f B r ). Already have that (more f B r ) is chop-star fixpoint: = (more f B r ) ( (more f B r ) ). Using time reversal ( of this: = finite (more f B r ) ( (more f B r ) ) ) r. Simplify: = finite f (more B) ( f (more B) ). Can extend proof to infinite time. 14

15 15 Reduction to Conventional Temporal Logic Want to show: f (more B) f (more B ) w. Example: In Peterson s algorithm, let w be cs 0 = 0 cs 1 = 0. Re-express w as f fin w. Can test validity for finite time. Readily extends to infinite time. Or test by reducing to finite time with point-based temporal logic: (more B) (more B ) fin w Temporal reverse of f (more B) reducible to PTL formula. Simplifies testing w As Sys Co fin w. Sys is like a regular expression and easy to reverse. In following, for any f formula only need to check for finite time: = w finite Sys f A fin w = w Sys ω f A fin w. Helps show f (more B) is chop-star fixpoint for infinite time.

16 Some Related Observations by Others Textbook using Duration Calculus (ITL variant for real time): Real-Time Systems: Formal Specification and and Automatic Verification E.-R. Olderog & H. Dierks, Cambridge University Press Regarding point-based logics: complicated reasoning Regarding timed process algebras: difficult to calculate with KIV interactive theorem prover at Univ. of Augsburg, Germany. Uses ITL as frontend and as backend for UML, Statecharts, etc. FACS journal paper, 2009 (lock-free algs., linearizability, Re/Gu): The (program s) line numbers... are not used in KIV. An additional translation to a special normal form (as e.g. in TLA) using explicit program counters is not necessary. 16

17 Conclusions We have presented some ideas about reasoning in ITL: Temporal fixpoints for sequential compositionality Prefix subintervals (instead of past-time constructs). Time reversal for reduction to point-based temporal logic. Reductions from infinite time to finite time. View point-based temporal logic as lower level and subordinate. Approach is intriguing (and axiomatisable) but needs further study. Appears related to Dijkstra s Gotos considered harmful thesis. Somewhat analogous to Vardi s Final Showdown article relating linear-time and branch-time temporal logics for model checking. For more about ITL: ITL webpages maintained by Antonio Cau: Using search engine: Interval Temporal Logic 17