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...ically interfaces of software components via static analysis has been discussed before, for modelchecking purposes (e.g., [8]), reverse engineering (e.g., [37]), and compositional verification (e.g., =-=[1]-=-). However, we are not aware of any tool like DART which combines automatic interface extraction with random testing and dynamic test generation. DART is complementary to test-management tools that ta...

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... implementations. As the implementation changes, the specification becomes increasingly incorrect. As a result, several researchers have been motivated to study the problem of specification inference =-=[3, 4, 11, 16, 17, 19, 40, 48, 49]-=-. Although early work in this area emphasized static analysis of the program text [3, 16, 19, 48], more recently several researchers have explored the possibility of using a program’s dynamic behavior...

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..., such as Amphion [13]. Turning to the technology enabling PROSPECTOR, mining the jungloid graph is related to work on extracting models from source code. Whaley, Martin, and Lam [15] and Alur et al. =-=[1]-=- extract temporal interfaces from Java source code by static analysis rather than mining. Jungloid mining is related to backward slicing [14, 4, 5] and program dependence graphs (PDGs), because a jung...

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...ence patterns with test failures [11]. Whaley et al. [34] hardcode a restricted model paradigm so that probable models of object-oriented interfaces can be easily automatically extracted. Alur et al. =-=[2]-=- generalize this to automatically produce small, expressive finite state machines with respect to certain predicates over an object. Lam et al. use a type system-based approach to statically extract i...

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..., pp. 461–476, 2005. c○ Springer-Verlag Berlin Heidelberg 2005s462 W. Weimer and G.C. Necula a variety of attempts have been made to infer program-specific temporal specifications and API usage rules =-=[1, 2, 7, 14]-=- automatically. These specification mining techniques take programs (and possibly dynamic traces, or other hints) as input and produce candidate specifications as output. In general, specifications co...

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...] is an elegant framework for specifying a class of temporal safety properties. Typestates can encode correct usage rules for many common libraries and application programming interfaces (APIs) (e.g. =-=[33, 2]-=-). For example, typestate can express the property that a Java program should not read data from java.net.Socket until the socket is connected. This paper addresses the challenge of typestate verifica...

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...cified API and learns usage scenarios and specifications among them. In our evaluation, we showed how our approach can mine specifications around those mined by their approach. A number of approaches =-=[3, 12, 24]-=- have been developed to apply static analysis or model checking on the API implementation code to synthesize permissive API usage patterns that are allowed by the API implementation. Different from th...

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... “a must not be followed by b” for Java method calls. Their technique relies on static analysis of a method’s implementation to find out if calling b after a would produce a runtime error. Alur et al =-=[1]-=- extend their method using model checking to handle sequences of calls σ and to provide additional soundness. Although powerful, these techniques examine the implementation of methods rather than the ...

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...lleviates the interlacement among different usages that are sensitive to programming contexts. The third category is to mine automata from API client code or traces. To mine automata, some approaches =-=[4, 5, 21]-=- use the Angluin’s algorithm [6], and other approaches [9, 11, 14, 28, 31, 36] adopt various customized techniques. These approaches are not as robust to noise (either an anomalous or buggy API method...