Lightweight object specification with typestates

Bierhoff, Kevin; Aldrich, Jonathan

doi:10.1145/1095430.1081741

Cited by 9 publications

(10 citation statements)

References 24 publications

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“…The specification method is based on linear logic, and relations among objects in the protocol are checked by a tailored system of permissions. Similarly, [15,10] provide a means to specify typestate properties that belong to a single object. The specified properties are reminiscent of contracts or method pre/post-conditions and can deal with inheritance.…”

Section: Related Workmentioning

confidence: 99%

Runtime Verification Based on Register Automata

Grigore

Distefano

Petersen

et al. 2013

Tools and Algorithms for the Construction and Analysis of Systems

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We propose TOPL automata as a new method for runtime verification of systems with unbounded resource generation. Paradigmatic such systems are object-oriented programs which can dynamically generate an unbounded number of fresh object identities during their execution. Our formalism is based on register automata, a particularly successful approach in automata over infinite alphabets which administers a finite-state machine with boundedly many inputstoring registers. We show that TOPL automata are equally expressive to register automata and yet suitable to express properties of programs. Compared to other runtime verification methods, our technique can handle a class of properties beyond the reach of current tools. We show in particular that properties which require value updates are not expressible with current techniques yet are naturally captured by TOPL machines. On the practical side, we present a tool for runtime verification of Java programs via TOPL properties, where the trade-off between the coverage and the overhead of the monitoring system is tunable by means of a number of parameters. We validate our technique by checking properties involving multiple objects and chaining of values on large open source projects.

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Section: Related Workmentioning

confidence: 99%

Runtime Verification Based on Register Automata

Grigore

Distefano

Petersen

et al. 2013

Tools and Algorithms for the Construction and Analysis of Systems

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“…The formalism of multiple object API protocols mined in this paper is inspired by the object specifications of several existing object-oriented typestate systems [19, 20]. Because typestates reflect how state changes of objects can affect valid method invocations, a typestate is an abstraction over concrete object states and can be characterized by the values of all fields of an object.…”

Section: Background: Object-oriented Typestatesmentioning

confidence: 99%

“…The state invariant is evaluated to test whether an object is in a particular state. Either statically checked [19] or dynamically checked [20], state invariants of typestates are evaluated for every method invocation: source state violations are flagged as precondition violations, and destination state violations are flagged as postcondition violations. Source states and destination states are actually treated as preconditions and postconditions of corresponding methods, respectively.…”

Section: Background: Object-oriented Typestatesmentioning

confidence: 99%

“…These typestate systems have been proven useful for modeling protocols in object-oriented programs [19, 20]. However, there are mainly two drawbacks of them to specify API protocols.…”

Section: Background: Object-oriented Typestatesmentioning

confidence: 99%

“…The observation behind typestates is that whether an operation is available on an object depends not only on the type of the object but also its internal states. Researchers develop several typestate systems for object-oriented programs [19, 20]. State abstraction techniques to mine typestates based on explicit object states [14, 15] have been proven effective to mine useful API protocols of single objects.…”

Section: Introductionmentioning

confidence: 99%

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Compositional Mining of Multiple Object API Protocols through State Abstraction

Dai

Mao

Lei

et al. 2013

The Scientific World Journal

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API protocols specify correct sequences of method invocations. Despite their usefulness, API protocols are often unavailable in practice because writing them is cumbersome and error prone. Multiple object API protocols are more expressive than single object API protocols. However, the huge number of objects of typical object-oriented programs poses a major challenge to the automatic mining of multiple object API protocols: besides maintaining scalability, it is important to capture various object interactions. Current approaches utilize various heuristics to focus on small sets of methods. In this paper, we present a general, scalable, multiple object API protocols mining approach that can capture all object interactions. Our approach uses abstract field values to label object states during the mining process. We first mine single object typestates as finite state automata whose transitions are annotated with states of interacting objects before and after the execution of the corresponding method and then construct multiple object API protocols by composing these annotated single object typestates. We implement our approach for Java and evaluate it through a series of experiments.

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