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Response Time Analysis of EQL Real-Time Rule-Based Systems
February 1995 (vol. 7 no. 1)
pp. 26-43

Abstract—Real-time rule-based expert systems are embedded decision systems that must respond to changes in the environments within stringent timing constraints. Given a program p, the response time analysis problem is to determine the response time of p. This problem consists of 1) determining whether or not the execution of p always terminates in bounded time, and 2) computing the maximal execution time of p.

The EQuational Logic (EQL) language is a simple language designed for real-time applications. It has been proved by Mok that the response time analysis problem is undecidable if the program variables have infinite domains, and is PSPACE-hard in the case where all of the variables have finite domains. However, we have observed that the use of a simple syntactic and semantic check on programs coupled with other techniques such as state space graph checks can dramatically reduce the time needed in the analysis. There are sets of syntactic and semantic constraint assertions such that if the set S of rules satisfies any of them, then the execution of S always terminates in bounded time. Each of these sets of syntactic and semantic constraint assertions is called a Special Form.

The focus of this paper is on proving the existence of two Special Forms and determining tight response time upper bounds of EQL rule-based programs. For each known Special Form, an algorithm used to calculate the maximal response time of programs satisfying this Special Form is presented. Additionally, to enhance the applicability of the proposed algorithms, we show how the General Analysis Algorithm can be used with these algorithms.

[1] S. Abiteboul and E. Simon, "Fundamental Properties of Deterministic and Nondeterministic Extensions of Datalog," Theoretical Computer Science, vol. 78, pp. 137-158, 1991.
[2] A.V. Aho,J.E. Hopcroft, and J.D. Ullman,The Design and Analysis of Computer Algorithms.Reading, Mass.: Addison-Wesley, 1974.
[3] A. Aiken, J. Widom, and J.M. Hellerstein, “Behavior of Database Production Rules: Termination, Confluence, and Observable Determination,” Proc. ACM SIGMOD Int'l Conf. Management of Data, M. Stonebraker, ed., pp. 59-68, May 1992.
[4] M. Benda,“Real-time applications of AI in the aerospace industry,” Presentation at the Fall School on Artificial Intelligence, The ResearchInst. ofÈcole Normal Superieure, France, Sept.4, 1987.
[5] D.A. Brant, T. Grose, B. Lofaso, and D.P. Miranker, “Effects of Database Size on Rule System Performance: Five Case Studies,” Proc. 17th Int'l Conf. Very Large Databases, 1991.
[6] J.C. Browne,A.M.K. Cheng, and A.K. Mok,“Computer-aided design of real-time rule-based decision systems,” Technical Report, Dept. of Computer Science, Univ. of Texas at Austin, April 1988. Also to appear in IEEE Trans. on Software Engineering.
[7] S. Ceri and J. Widom,"Deriving production rules for incremental view maintenance," Proc. 17th VLDB, pp. 735-749,Barcelona, 1991.
[8] J.R. Chen and A.M.K. Cheng,“A classification scheme to facilitate thedetermination of the property of execution termination of equationalrule-based programs,” Internal report submitted to 1994 Symp. on Foundations of Computer Science.
[9] A.M.K. Cheng,J.C. Browne,A.K. Mok,, and R.-H. Wang,“Estella: A language for specifying behavioral constraint assertions in real-time rule-basedsystems,” 6th Ann. IEEE Conf. on Computer Assurance, Nat’l Inst. Standards and Tech nology, Gaithersburg, Md., June 1991.
[10] A.M.K. Cheng, J.C. Browne, A.K. Mok, and R.-H. Wang, "Analysis of Real-Time Rule-Based System with Behavioral Constraint Assertions Specified in Estella," IEEE Trans. Software Eng., vol. 19, no. 9, pp. 863-885, Sept. 1993.
[11] A.M.K. Cheng and C.-H. Chen,“Efficient response time bound analysis of real-time rule-based systems,” Proc. IEEE COMPASS’92, June 1992.
[12] A.M.K Cheng and C.-K Wang,“Fast static analysis of real-time rule-based systems to verify their fixed point convergence,” Proc. of the Fifth Ann. Conf. on Computer Assurance, pp. 46-56, 1990.
[13] E.M. Clarke, E.A. Emerson, and A.P. Sistla, "Automatic verification of finite-state concurrent systems using temporal logic specifications," ACM Trans. Programming Languages and Systems, vol. 8, no. 2, pp. 244-263, 1986.
[14] C.L. Forgy,OPS5 User’s Manual, Technical Report CMU-81-135, Dept. Computer Science, Carnegie-Mellon University,1981.
[15] M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness.New York: W.H. Freeman, 1979.
[16] J.J. Helly, “Distributed expert system for space shuttle flight control,” Ph.D. Dissertation, Dept. Computer Science, UCLA, 1984.
[17] T. Ishida,“Parallel rule firing in production systems,” IEEE Trans. on Knowledge and Data Engineering, vol. 3, No. 1, pp 11-17, March 1991.
[18] T. Ishida and S.J. Stolfo,’Towards the parallel execution of rules in production systemprograms,” Proc. of the 1985 Int’l Conf. on Parallel Processing, pp 568-575, 1985.
[19] D. Koch,K. Morris,C. Giffin,, and T. Reid,“Avionic sensor-based safing system technology,” Presentation at the Tri-Service Software System SafetyWorking Group in association with IEEE COMPASS Conf., 1986.
[20] C.-M. Kuo,D.P. Miranker,, and J.C. Browne,“On the performance of the CREL system,” J. of Parallel and Distributed Computing, vol. 13, No. 4, pp. 424-441, Dec. 1991.
[21] S. Kuo and D. Moldovan,“Implementation of multiple rule firing production systems on hypercube,” J. of Parallel and Distributed Computing, vol. 13, No. 4, pp. 383-394, Dec. 1991.
[22] T.J. Laffey,P.A. Cox,J.L. Schmidt,S.M. Kao, and J.Y. Read,"Real-time knowledge-based systems," AI Magazine, pp. 27-45, Spring 1988.
[23] J.S. Lark,L.D. Erman,S. Forrest,K.P. Gostelow,F. Hayes-Roth,, and D.M. Smith,“Concepts, methods, and languages for building timely intelligent systems,” J. Real-Time Systems, vol. 2, pp. 127-148, May 1990.
[24] C.A. Marsh,“The ISA expert system: a prototype system for failure diagnosis on the space station,” MITRE Report, The MITRE Corporation, Houston, Tex., 1988.
[25] A.K. Mok, "Formal Analysis of Real-Time Equational Rule-Based Systems," Proc. RTSS, 10th Real-Time Systems Symp., Dec. 1989.
[26] C.A. O’Reilly and A.S. Cromarty,“’Fast’is not’real-time’: designing effective real-time AI systems,” Applications of Artificial Intelligence, John F. Gilmore, ed., Proc. of SPIE, 1985.
[27] D.W. Payton and T.E. Bihari,“Intelligent real-time control of robotic vehicles,” Comm. of the ACM, vol. 34, No. 8, pp. 48-63, Aug. 1991.
[28] J.G. Schmolze,“Guaranteeing serializable results in synchronous parallelproduction systems,” J. of Parallel and Distributed Computing, vol. 13, No. 4, pp. 348-365, Dec. 1991.
[29] S.J. Stolfo,O. Wolfson,P.K. Chan,H.M. Dewan,L. Woodbury,J.S. Glazier,, and D.A. Ohsie,“PARULEL: Parallel rule processing using meta-rules forredaction,” J. of Parallel and Distributed Computing, vol. 13, No. 4, pp.366-382, Dec. 1991.
[30] C.-K. Wang and A.K. Mok, "Timing Analysis of MRL: A Real-Time Rule-Based System," J. Real-Time Systems, vol. 5, no. 1, pp. 89-128, Mar. 1993.
[31] M. Jarke, J. Mylopoulos, J.W. Schmidt, and Y. Vassiliou, "DAIDA: An Environment for Evolving Information Systems," ACM Trans. Information Systems, pp. 1-50, vol. 10, Jan. 1992.
[32] B. Zupan and A.M.K. Cheng,“Optimization of rule-based systems via state transition system construction,” Proc. of 1994 IEEE Conf. on Artificial Intelligence for Applications, pp. 320 - 326, March 1994.

Index Terms:
Computer aided software engineering, real-time decision systems, response time, rule-based programs, special forms, verification.
Citation:
Jeng-Rung Chen, Albert Mo Kim Cheng, "Response Time Analysis of EQL Real-Time Rule-Based Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 7, no. 1, pp. 26-43, Feb. 1995, doi:10.1109/69.368520
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