This paper describes a formal change impact analysis approach for systematic evolution of communicating systems. Systems are modeled using a network of communicating extended finite state machines (CEFSMs) with variables ranging over commonly used data types including numbers, booleans, arrays, and object fields. Parameterized messages exchanged over queues and shared variables are used for communication. Changes to the system are performed at the transition level by adding/deleting transitions. Given a changed transition, the impacted system transitions are automatically computed using a bounded, selective, state exploration based on the inductive assertion approach. A theorem prover extended with queue axioms is used to discharge the verification conditions. Multiple symbolic values for each variable present in a system state are represented as a set of rewrite rules to minimize state space overheads. Rewrite-rule based procedures are described for reducing the number of symbolic values in system states. We also describe heuristics to identify simultaneously enabled and disabling transitions and describe a procedure to reduce the number of verification conditions generated during the impact analysis. The effectiveness of the proposed approach is illustrated on several applications including web services and cache coherence protocols.

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Aiming at the low efficiency and high energy consumption of unmanned ships traversing the entire area, a complete coverage path planning algorithm based on the improved A-star algorithm is proposed. The positioning and vision systems of unmanned ships are used to digitize the actual water information, and the grid method is used to convert the information into an environmental map that can be planned. Compared to the trapezoidal partition of unity method and the short-side reciprocating traversal algorithm in the traversal process, experiments show that path planning is more efficient with the boustrophedon partition of unity method and the long-side reciprocating traversal algorithm. Aiming at the “dead zone”, an improved A-star algorithm is proposed on the basis of the traditional A-star algorithm, that it can shorten about 1/4 path using the proposed algorithm. Simulation shows that the improved A-star algorithm can shorten the traversal path to 40 steps but the traditional A-star algorithm needs 54 steps. Navigation test shows that the proposed algorithm can shorten the traversal path and improve traversal efficiency while ensuring the coverage of unmanned ships.

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A formal approach to select tests for regression testing of changes performed in a system evolution step is proposed. Systems are modeled as extended finite state machines (EFSMs) supporting several commonly used data types including booleans, numbers, arrays, queues and records. Tests are described using a sequence of input and expected output messages with concrete parameter values. Changes add/delete/replace one or more EFSM transitions. Transitions potentially executed by a test are automatically identified from its description. A simple structural invariant for a test description based on these transitions is introduced. It is shown that for a test description satisfying the invariant it can be accurately determined if a given change affects the test. Affected tests are selected for regression testing of the change. Failure of a description to meet the invariant is analyzed to identify non-observable regions in the description, which are then further analyzed using other system transitions to identify affected tests. We also describe a novel approach based on substitutability of tests to reduce the size of a regression test suite without affecting coverage. The effectiveness of the proposed approach is illustrated by applying it to several examples. Our experiments based on a well-known cost model for regression testing show that the proposed approach is economical for selective re-testing in these examples.