This paper presents the overal structure, the design criteria, and the main features of the tool box Uppaal. It gives a detailed user guide which describes how to use the various tools of Uppaal version 2.02 to construct abstract models of a real-time system, to simulate its dynamical behavior, to specify and verify its safety and bounded liveness properties in terms of its model. In addition, the paper also provides a short review on case-studies where Uppaal is applied, as well as references to its theoretical foundation.

UPPAAL in a Nutshell

https://www.cis.upenn.edu/~alur/TCS95.pdf

The algorithmic analysis of hybrid systems

We summarize several recent results about hybrid automata. Our goal is to demonstrate that concepts from the theory of discrete concurrent systems can give insights into partly continuous systems, and that methods for the verification of finite-state systems can be used to analyze certain systems with uncountable state spaces.

The theory of hybrid automata

This paper introduces the concept of a hybrid system and some of the challenges associated with the stability of such systems, including the issues of guaranteeing stability of switched stable systems and finding conditions for the existence of switched controllers for stabilizing switched unstable systems. In this endeavour, this paper surveys the major results in the (Lyapunov) stability of finite-dimensional hybrid systems and then discusses the stronger, more specialized results of switched linear (stable and unstable) systems. A section detailing how some of the results can be formulated as linear matrix inequalities is given. Stability analyses on the regulation of the angle of attack of an aircraft and on the PI control of a vehicle with an automatic transmission are given. Other examples are included to illustrate various results in this paper.

Perspectives and results on the stability and stabilizability of hybrid systems

In this paper, we propose a method for the automatic construction of an abstract state graph of an arbitrary system using the Pvs theorem prover.

/pdf/construction-of-abstract-state-graphs-with-pvs-1t340arenf.pdf

Construction of Abstract State Graphs with PVS

We present a new abstraction refinement algorithm to better refine the abstract model for formal property verification. In previous work, refinements are selected either based on a set of counter examples of the current abstract model, as in [5][6][7][8][9][19][20], or independent of any counter examples, as in [17]. We (1) introduce a new "controllability" analysis that is independent of any particular counter examples, (2) apply a new "cooperativeness" analysis that extracts information from a particular set of counter examples and (3) combine both to better refine the abstract model. We implemented the algorithm and applied it to verify several real-world designs and properties. We compared the algorithm against the abstraction refinement algorithms in [19] and [20] and the interpolation-based reachability analysis in [14]. The experimental results indicate that the new algorithm outperforms the other three algorithms in terms of runtime, abstraction efficiency (as defined in [19]) and the number of proven properties.

Abstraction refinement by controllability and cooperativeness analysis

Relates to automatic conversion of assumption constraints, used in circuit design verification, that model an environment for testing a DUT/DUV, where the assumptions specify sequential behavior. Such assumptions are converted, with the use of logic synthesis tools, into a gate-level representation. For formal verification, a verification output is constructed from the gate-level representation and DUT/DUV assertion-monitoring circuitry. A formal verifier seeks to prove the verification output cannot indicate a design error. For simulation verification, the gate-level representation is converted into a hybrid representation comprising pipelines and combinational constraints. During simulation, the pipelines hold state information necessary for a solution, of the combinational constraints, to be in accord with the sequential assumption constraints. For certain sequential assumption constraints, the combinational constraints are insufficient to insure avoidance of deadend states. In a deadend state, an assumption is violated. A method is presented for augmenting the combinational constraints to avoid deadend states.

Method and apparatus for solving sequential constraints

System, methods, and apparatus for verifying microcircuit designs by interleaving between random and formal simulation techniques to identify input traces useful for driving designs under test into sequences of device states. In a method aspect the invention provides process for beginning random simulation of a sequence of states of a microcircuit design by inputting a sequence of random input vectors to a design under test model in order to obtain a sequence of random simulation states; monitoring a simulation coverage progress metric to determine a preference for switching from random simulation to formal methods of simulating states in the design under test; beginning formal simulation of states in the design under test and monitoring a formal coverage progress metric to determine a preference for resuming random simulation of states of said microcircuit design; and resuming random simulation. Preferably the process of interleaving simulation methods continues until an input vector suitable for driving the design under test model into each of a set of previously-identified goal states has been obtained.

Simulation-based functional verification of microcircuit designs

A set of vertices D is a dominating set of a graph $G = ( V,E )$ if every vertex in $V - D$ is adjacent to a vertex in D. The domatic number $d ( G )$ of a graph $G = ( V,E )$ is the maximum number k such that V can be partitioned into k disjoint dominating sets $D_1 , \cdots ,D_k $. The main purpose of this paper is to give linear algorithms for the domatic number problem in interval graphs. This paper also proves that $d ( G ) = \delta ( G ) + 1$ for any interval graph G, where $\delta ( G )$ is the minimum degree of a vertex in G.

/pdf/the-domatic-number-problem-interval-graphs-feb9awogtc.pdf

The domatic number problem interval graphs

/pdf/model-checking-strategies-for-linear-hybrid-systems-4pzkznazmk.pdf

Pei-Hsin Ho

Papers

Abstraction refinement by controllability and cooperativeness analysis

Method and apparatus for solving sequential constraints

Simulation-based functional verification of microcircuit designs

The domatic number problem interval graphs

Model Checking Strategies for Linear Hybrid Systems