MONAA: a Tool for Timed Pattern Matching with Automata-Based Acceleration

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1 MONAA: a Tool for Timed Pattern Matching with Automata-Based Acceleration Masaki Waga 1, Ichiro Hasuo 1, and Kohei Suenaga 2 National Institute of Informatics 1 and Kyoto University 2 10 Apr. 2018, MT-CPS 2018 The authors are supported by ERATO HASUO Metamathematics for Systems Design Project (No. JPMJER1603), JST, Grants-in-Aid No. 15KT0012, JSPS, and JST PRESTO Grant Number JPMJPR15E5, Japan. 1

2 Timed Pattern Matching Input Time-series data (Logs of a car/ a robot) e.g., The gear of a car is high at 0.1s, at 0.3s, Timed Words high high (Sequence of events with timestamps) w = t Real-time spec. (Spec. useful for debugging) Output [Ulus et al., FORMATS 14] e.g., The gear of a car changes too frequently high,x<1 A = s 0 Timed Automata [Alur & Dill, TCS 94] The intervals where the spec. is satisfied in the data e.g., The gear M(w, changes A) ={(t, too frequently t 0 ) w (t,t0 in ) 20.3s-0.7s L(A)} $,x<1 start s 1 s 2 s 3,x<1 2

3 MONAA Overview Command Line Interface (MONAA) Command line tool for timed pattern matching We can inspect a log The log is read lazily online monitor Text-based I/O C++ API (libmonaa) Execute timed pattern matching in a user s code Accelerated by Skipping [Waga et al., FORMATS 17] I/O by function/class 3

4 Outline 1. Algorithm in MONAA Skipping for timed pattern matching [Waga et al., FORMATS 17] 2. Frontend of MONAA Command line interface (CLI) / C++ API 3. Experiments 4

5 Skipping for String Matching STRONG_STRING STRING Find STRING (pattern) STRING from STRONG_STRING (target) STRING Brute-Force Search KMP Search [Knuth+, SIAM J. Comput. 77] S T R Match until the 3rd char. Table for length 3 partial match I N G * S T R I N * * S T R I * * * S T R 5 STRONG_STRING STRING STRING STRING STRING STRING Skip 2 trials!!

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sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">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</latexit> <latexit sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">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</latexit> Find from Brute-Force Algorithm for Timed Pattern Matching w = 1st trial 2nd trial A = high,x<1 start s $,x<1 0 s 1 s 2 s 3 high s 3,x<1 high s 0 s 1 s 2 s 1 s 2 s 0 8 >< t 2 [0, 0.1) t >: 0 2 (0.3, 0.5] t 0 t 2 (0, 1) s 3 (pattern) (target) 1.2 t 8 >< t 2 [0, 0.1) t >: 0 2 (0.7, 1.1] t 0 t 2 (0, 1) 3rd trial s 0 s 1 s 2 s 1 8 >< t 2 [0.3, 0.5) s 3 t >: 0 2 (0.7, 1.2] M. t 0 Waga t 2 (0, (NII) 1) 6

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sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">aaacnnicbzbbt9swfmcdbhslbhtjymwimgcpi5xueztwcogcxcqkse1uoc5lseo4kf0yqyr6qxbz59itfw6gadd9bnyqw4a9ydjfv/97tt8/kzw0ynjcw3mxuvby1fprf2pzzdutzrv3f7aojichkfrhrhjuquknq5so4ko0wpnewwuypv76l9/bwfnoc5yveod8omumbuehxp3tkigj1lvwd9i5jzssmo5y8knhgi8huetjxop2wxdyc4n+3kcp2mjeeobhonn2ftzpsoa1rz+lsbvd0tbzupmrsgtr5abrkg7tkgqlxju3kiwcur9vfkoupnwciyc1z8hgdbp2nh5wjkvzydzrsbv670tnc2tneei6c47x9qm3hp/zrhvmx+na6rjc0olhoaxsfau6zjcm0obanxoccypdx6m45oylden7lotw6crpxuu/cfkqfvvchry1caythbjl9klidsmanjazmisc/calckvuvj/ejffb+/pquuk1m9vkuxl/7wgykaz0</latexit> <latexit sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">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</latexit> <latexit sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">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</latexit> <latexit sha1_base64="g8/sgkr0wuuzx9mbyjbujor1qve=">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</latexit> Find from KMP-Style Algorithm for Timed Pattern Matching w = 1st trial Skip 1 trial!! 2nd trial A = high,x<1 start s $,x<1 0 s 1 s 2 s 3 high s 3,x<1 high s 0 s 1 s 2 s 1 s 2 s 0 8 >< t 2 [0, 0.1) t >: 0 2 (0.3, 0.5] t 0 t 2 (0, 1) s 3 (pattern) (target) 1.2 t 8 >< t 2 [0, 0.1) t >: 0 2 (0.7, 1.1] t 0 t 2 (0, 1) 2nd trial s 0 s 1 s 2 s 1 8 >< t 2 [0.3, 0.5) s 3 t >: 0 2 (0.7, 1.2] M. t 0 Waga t 2 (0, (NII) 1) 7

8 Problems in Skipping for Timed Pattern Matching The length of partial match is unbounded. String Matching Table for length 3 partial match S T R I N G * S T R I N * * S T R I * * * S T R Length 3 partial match in string matching S T R We construct for each length Infinitely many timestamps String Matching 8 Timed Pattern Matching Infinitely Many Tables!! Timed Pattern Matching Length 2 partial match in timed pattern matching 0 high Infinitely many timestamps t

9 Problems in Skipping for Timed Pattern Matching The length of partial match is unbounded. String Matching Table for length 3 partial match S T R I N G * S T R I N * * S T R I * * * S T R Infinitely many timestamps String Matching Length 3 partial match in string matching S T R Construct for each state Represent by a timed automaton Timed Pattern Matching Table for state s2 partial match 0 0 high 0 Timed Pattern Matching t high t high State s2 partial match in timed pattern matching high,x<1 s start 0 s 1 s 2,x<1 t 9

10 Problems in Skipping for Timed Pattern Matching The length of partial match is unbounded. Table for length 3 partial match S T R I N G * S T R I N * * S T R I * * * S T R Infinitely many timestamps Length 3 partial match in string matching S T R Construct for each state Represent by a timed automaton Table for state s2 partial match 0 0 high 0 State s2 partial match in timed pattern matching t high t high high,x<1 s start 0 s 1 s 2,x<1 t 10

11 Skipping for Timed Pattern Matching Table for state s2 partial match high,x<1 s start 0 s 1 s 2 high/x := 0,x<1 start s 1 s 0 s 1 s 2 /x := 0 high,x<1,x<1 We want to compare them high high/x := 0 high,x<1 start s 2 s 1 s 0 s 1 s 2 /x := 0,x<1 11

12 Skipping for Timed Pattern Matching Table for state s2 partial match high,x<1 s start 0 s 1 s 2 high/x := 0,x<1 start s 1 s 0 s 1 s 2 /x := 0 high,x<1,x<1 Product Emptiness Checking high high/x := 0 high,x<1 start s 2 s 1 s 0 s 1 s 2 /x := 0,x<1 12

13 Emptiness Checking by Zone Construction Labelled by a set of similar clock valuations represented by a zone s 1 a, x < 1 $,x>1 construct an NFA a s 1 0 <x<1 $ s 3 x>1 start s 0 s 3 start s 0 x =0 b b, x =1/x := 0 s 2 $, x<1 s 2 x =0 $ s 3 0 <x<1 Thm. (soundness and completeness) Zone automata maintain state reachability. 13

15 Input of MONAA (CLI) 15

16 Output of MONAA (CLI) 16

17 C++ API (libmonaa) User s Program e.g., online runtime verification C++ API (libmonaa) Get feedback Give Logs Execute timed pattern matching in a user s code Accelerated by Skipping I/O by function/class 17

18 Better Performance by libmonaa MONAA libmonaa Compile monaa TA/TRE Exec. Result Timed Word libmonaa (TA is hard-coded) libmonaa Compile Monitor TA Exec. Result More optimization!! Timed Word 18

20 Comparison with Montre MONAA Use timed automata We can also construct a TA from a TRE Accelerated by skipping Both command line and C++ interface Existing Tool (Montre) [Ulus, CAV 17] Use timed regular expression (online) On-the-fly construction of a state machine from TRE Only command line interface Our algorithm should work faster because of skipping

21 Experiments Monitoring of a Simulink model of an automatic transmission in a car. Model and spec. are from an automotive benchmark paper [Hoxha et al., ARCH 15] Events: gears: g1,g2,g3,g4 velocity: v >v, v v RPM: ω > ω, ω ω 21

22 Experiments Gear changes from g1 to g4 in 10 sec. and RPM changes to high enough, but velocity is still. g 1 g 2, true g 2 g 3, true g 3 g 4,xapple 10 /x := 0 g 4 3 g 1, true start?!!, true!!, true!!, true!!, true $,x>1!!, true? g 1, true g 2, true g 3, true g 1 g 2 g 3 g 4 g 4,xapple 10 /x := 0 22

23 Result of the Comparison Length of timed word Table 1. Execution time (sec.) MONAA (TRE) MONAA (TA) libmonaa (TA is hard coded) Montre (online) Montre (offline) , , , , , , , ,011, Efficient and online B up!! Efficient but offline only 23

24 Conclusion MONAA can inspect logs with timestamps fast (skipping) simple (text-based I/O) flexible (C++ API) 24

25 Future Works Theoretical Side: Investigate other techniques for efficient monitoring Practical Side: Case study of timed pattern matching 25