Scenario-based and value-based specification mining: better together

Lo, David; Maoz, Shahar

doi:10.1007/s10515-012-0103-x

Cited by 49 publications

(44 citation statements)

References 55 publications

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“…There are other ways to aid development tasks than inferring models, such as detecting method invocation patterns [20,48] and inter-object sequence charts [26,31]. These patterns can detect code anomalies [21,37].…”

Section: Related Workmentioning

confidence: 99%

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Automatic mining of specifications from invocation traces and method invariants

Krka

Brun

Medvidović

2014

Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

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Software library documentation often describes the APIs of individual methods, but does not capture the intended protocols and method interactions. This can cause developers to misuse the library by invoking its methods out of sequence, while also restricting effective runtime detection of protocol violations and automated verification of the client code. Specification mining, if accurate, can help mitigate these problems. There are two classes of specification mining techniques: one that observes library executions, and another that identifies internal-state invariants. Unfortunately, models inferred by these state-of-the-art techniques often suffer from inaccuracies. In this paper, we aim to improve the quality of mined specifications in order to facilitate API understanding, test generation, and verification tasks. To that end, we combine the two classes of techniques in two novel ways, producing a pair of new model-inference techniques. We find that our new techniques improve significantly upon the state-of-the-art when applied to nine off-the-shelf libraries, increasing the precision of the inferred models by 4% and the recall by 41% on average. Additionally, we find that our approach automatically exposes both behavior that avoids raising exceptions and good-practice rules that capture proper library use, while being robust to noisy inputs.

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Section: Related Workmentioning

confidence: 99%

“…These patterns can detect code anomalies [21,37]. Scenario-based views of a system's behavior, such as parametrized [31] and symbolic [26] sequence charts, facilitate understanding of a system's runtime interactions.…”

Section: Related Workmentioning

confidence: 99%

Automatic mining of specifications from invocation traces and method invariants

Krka

Brun

Medvidović

2014

Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

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“…This kind of inference is dual to ours, in the sense that we infer contracts in a top-down approach, in order to express what conditions individual components should fulfill inside a broader system, while the works mentioned above are bottom-up, encapsulating the behavior of actual code in contracts in order to check whether callers can use this particular implementation. The same can be said of works that aim at generating transition systems modeling the behavior of programs, either as message sequence charts as in [16], or as scenarios expressed under the form of live sequence charts, as in [17].…”

Section: Related Workmentioning

confidence: 99%

Model-Based Testing from Input Output Symbolic Transition Systems Enriched by Program Calls and Contracts

Boudhiba

Gaston

Gall

et al. 2015

Testing Software and Systems

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Abstract. An Input Output Symbolic Transition System (IOSTS) specifies all expected sequences of input and output messages of a reactive system. Symbolic execution over this IOSTS then allows to generate a set of test cases that can exercise the various possible behaviors of the system it represents. In this paper, we extend the IOSTS framework with explicit program calls, possibly equipped with contracts specifying what the program is supposed to do. This approach bridges the gap between a model-based approach in which user-defined programs are abstracted away and a code-based approach in which small pieces of code are separately considered regardless of the way they are combined. First, we extend symbolic execution techniques for IOSTS with programs, in order to re-use classical test case generation algorithms. Second, we explore how constraints coming from IOSTS symbolic execution can be used to infer contracts for programs used in the IOSTS.

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“…In effect, this could be viewed as an integration of this work with our previous work in [24], which proposes an approach to zoomin and -out mined specifications. In [25], we introduce mining scenario-based specifications with value-based invariants involving method parameters. In this work, we focus on LSCs without value-based invariants.…”

Section: Related Workmentioning

confidence: 99%

Towards Succinctness in Mining Scenario-Based Specifications

Maoz

2011

2011 16th IEEE International Conference on Engineering of Complex Computer Systems

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Abstract-Specification mining methods are used to extract candidate specifications from system execution traces. A major challenge for specification mining is succinctness. That is, in addition to the soundness, completeness, and scalable performance of the specification mining method, one is interested in producing a succinct result, which conveys a lot of information about the system under investigation but uses a short, machine and humanreadable representation.In this paper we address the succinctness challenge in the context of scenario-based specification mining, whose target formalism is live sequence charts (LSC), an expressive extension of classical sequence diagrams. We do this by adapting three classical notions: a definition of an equivalence relation over LSCs, a definition of a redundancy and inclusion relation based on isomorphic embeddings among LSCs, and a deltadiscriminative measure based on an information gain metric on a sorted set of LSCs. These are applied on top of the commonly used statistical metrics of support and confidence.A number of case studies show the utility of our approach towards succinct mined specifications.

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Scenario-based and value-based specification mining: better together

Cited by 49 publications

References 55 publications

Automatic mining of specifications from invocation traces and method invariants

Automatic mining of specifications from invocation traces and method invariants

Model-Based Testing from Input Output Symbolic Transition Systems Enriched by Program Calls and Contracts

Towards Succinctness in Mining Scenario-Based Specifications

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