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=== Improvements to the ProB Constraint solver and empirical evaluation === | === Improvements to the ProB Constraint solver and empirical evaluation === | ||
Various industrial applications have shown the need for improved constraint-solving capabilities (see CBC Deadlock, Test-Case Generation). | |||
We have studied to what extent classical constraint satisfaction problems can be conveniently expressed as B predicates, and then solved by ProB. | |||
We study problems such as the n-Queens problem, graph colouring, graph isomorphism detection, time tabling, Sudoku, Hanoi, magic squares, Alphametic puzzles, and several more. | |||
We have also compared the performance with respect to other tools, such as the model checker TLC for TLA+, AnimB for Event-B, and Alloy. | |||
The experiments show that some constraint satisfaction problems can be expressed very conveniently in B and solved very effectively with ProB. | |||
For example, TLC takes 8747 seconds () to solve 9 queens expressed as a logical predicate; Alloy with minisat takes 0.406 seconds, ProB 1.3.3 takes 0.01 seconds. For 32 queens, ProB 1.3.3 takes 0.28 seconds, whicle Alloy with minisat takes over 4 minutes. | |||
Some problems, such as Hanoi, can also be more easily expressed and solved as a model checking problem (rather than as finding solutions to predicates). | |||
For some others, the performance of \prob\ is still sub-optimal with respect to, e.g., Alloy, and we will describe how we plan to overcome this shortcoming in the future. | |||
Our long term goal is that B can not only be used to as a formal method for developing safety critical software, but also as a high-level constraint programming language. | |||
=== Constraint-Based Deadlock Checking === | === Constraint-Based Deadlock Checking === |
Revision as of 09:14, 29 November 2010
Model Animation
Overview
Siemens Application
The most important additions of the last 12 months are:
- Application of ProB in three active deployments, namely the upgrading of the Paris Metro Line 1 for driverless trains, line 4 of the S\~{a}o Paulo metro and line 9 of the Barcelona metro. We also briefly report on experiments on the models of the CDGVAL shuttle. The paper [1] only contained the initial San Juan case study, which was used to evaluate the potential of our approach.
- In this article we describe the previous method adopted by Siemens in much more detail, as well as explaining the performance issues with Atelier B.
- Comparisons and empirical evaluations with other potential approaches and alternate tools (Brama, AnimB, BZ-TT and TLC) have been conducted.
- We provide more details about the ongoing validation process of ProB, which is required by Siemens for it to use ProB to replace the existing method.
The validation also lead to the discovery of errors in the English version of the Atelier B reference manual.
Also, since [2], ProB itself has been further improved inspired by the application, resulting in new optimisations in the kernel (see below).
More details:
Multi-level Animation
(ABZ'2010 & SCP journal paper)
Improvements to the ProB Constraint solver and empirical evaluation
Various industrial applications have shown the need for improved constraint-solving capabilities (see CBC Deadlock, Test-Case Generation). We have studied to what extent classical constraint satisfaction problems can be conveniently expressed as B predicates, and then solved by ProB. We study problems such as the n-Queens problem, graph colouring, graph isomorphism detection, time tabling, Sudoku, Hanoi, magic squares, Alphametic puzzles, and several more. We have also compared the performance with respect to other tools, such as the model checker TLC for TLA+, AnimB for Event-B, and Alloy.
The experiments show that some constraint satisfaction problems can be expressed very conveniently in B and solved very effectively with ProB. For example, TLC takes 8747 seconds () to solve 9 queens expressed as a logical predicate; Alloy with minisat takes 0.406 seconds, ProB 1.3.3 takes 0.01 seconds. For 32 queens, ProB 1.3.3 takes 0.28 seconds, whicle Alloy with minisat takes over 4 minutes.
Some problems, such as Hanoi, can also be more easily expressed and solved as a model checking problem (rather than as finding solutions to predicates). For some others, the performance of \prob\ is still sub-optimal with respect to, e.g., Alloy, and we will describe how we plan to overcome this shortcoming in the future. Our long term goal is that B can not only be used to as a formal method for developing safety critical software, but also as a high-level constraint programming language.
Constraint-Based Deadlock Checking
Ensuring the absence of deadlocks is important for certain applications, in particular for Bosch's Adaptive Cruise Control. We are tackling the problem of finding deadlocks via constraint solving rather than by model checking. Indeed, model checking is problematic when the out-degree is very large. In particular, quite often there can be a practically infinite number of ways to instantiate the constants of a B model. In this case, model checking will only find deadlocks for the given constants chosen.
Idea: solve constraints of axioms, invariant together with a constraint specifying a deadlock.
Required Developments:
- implementation of the algorithm, with semantic relevance filtering (to be able to restrict the deadlock search to certain scenarios: in Bosch's case due to the flow plugin, one wants to restrict deadlock checking e.g. to states with the variable Counter set to 10).
- Improvements to ProB's constraint solving engine: (reification of constraints, more precise information propagation for membership constraints, performance improvments in the typchecker and other parts of the kernel)
Success: Model 1 and Model 2: CrCtrl_Comb2Final; relevance of Counter=10 due to flow
Deadlock Freedom PO: 34 pages of ASCII, could not be loaded in Rodin "Java Heap Space Error". Counter examples found for 8 versions in 1-18 seconds.
BMotionStudio for Industrial Models
Lukas Ladenberger's Master's thesis
Various other improvements
mainly inspired by Siemens and Bosch Applications
Improved AVL algorithms, more operators
record support, treatment of infinite sets,
Motivations
The above works were motivated mainly to support the following three industrial deployments:
- Siemens: enable Siemens to use ProB in their SIL4 development chain, replacing Atelier B for data validation.
- Bosch: provide animation and constraint-based deadlock detection for the Adaptive Cruise Control
- SAP: provide a way to generate test cases using constraint-based animation
Available Documentation
References
Planning
- Finish Validation Report
- Write up Constraint-Based Deadlock Checking and integrate fully into Rodin Platform
- Support mathematical extensions in ProB