Supporting incremental behaviour model elaboration

Uchitel, Sebastián; Alrajeh, Dalal; Ben-David, Shoham; Braberman, Vı́ctor; Chećhik, Marsha; Caso, Guido de; D’Ippolito, Nicolás; Fischbein, Dario; Garbervetsky, Diego; Kramer, Jeff; Russo, Alessandra; Sibay, German

doi:10.1007/s00450-012-0233-1

Cited by 12 publications

(5 citation statements)

References 41 publications

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“…Partial knowledge has been considered in requirement analysis and elicitation [39,38,33], in novel robotic planners [34,35], and in the production of software models that satisfy a set of desired properties [50,49,18,1]. Several researchers analyzed the model checking problem for partially specified systems [37,11], some considering three-valued [32,22,8,9,24], others multivalued [26,10] scenarios.…”

Section: Related Workmentioning

confidence: 99%

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Menghi

Rizzi

Bernasconi

2020

Fundamental Approaches to Software Engineering

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System development is not a linear, one-shot process. It proceeds through refinements and revisions. To support assurance that the system satisfies its requirements, it is desirable that continuous verification can be performed after each refinement or revision step. To achieve practical adoption, formal system modeling and verification must accommodate continuous verification efficiently and effectively. Our proposal to address this problem is TOrPEDO, a verification approach where models are given via Partial Kripke Structures (PKSs) and requirements are specified as Linear-time Temporal Logic (LTL) properties. PKSs support refinement, by deliberately indicating unspecified parts of the model that are later completed. We support verification in two complementary forms: via model checking and proofs. Model checking is useful to provide counterexamples, i.e., pinpoint model behaviors that violate requirements. Proofs are instead useful since they can explain why requirements are satisfied. In our work, we introduce a specific concept of proof, called topological proof (TP). A TP produces a slice of the original PKS which justifies the property satisfaction. Because models can be incomplete, TOrPEDO supports reasoning on requirements satisfaction, violation, and possible satisfaction (in the case where the satisfaction depends on unknown parts).

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Section: Related Workmentioning

confidence: 99%

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Menghi

Rizzi

Bernasconi

2020

Fundamental Approaches to Software Engineering

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“…Different operations have been defined over MTS, such as (classical) refinement, observational refinement [CBFU06], model merging (or logical conjunction) [LSW95]. A good overview of this area is given in [UABD+13]. PLTS differ from MTS because they express incompleteness via black-box states which are placeholders for (possibly partial) components, instead of via transitions.…”

Section: Related Workmentioning

confidence: 99%

A verification-driven framework for iterative design of controllers

et al. 2019

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Controllers often are large and complex reactive software systems and thus they typically cannot be developed as monolithic products. Instead, they are usually comprised of multiple components that interact to provide the desired functionality. Components themselves can be complex and in turn be decomposed into multiple sub-components. Designing such systems is complicated and must follow systematic approaches, based on recursive decomposition strategies that yield a modular structure. This paper proposes FIDDle-a comprehensive verification-driven framework which provides support for designers during development. FIDDle supports hierarchical decomposition of components into sub-components through formal specification in terms of pre-and post-conditions as well as independent development, reuse and verification of sub-components. The framework allows the development of an initial, partially specified design of the controller, in which certain components, yet to be defined, are precisely identified. These components can be associated with pre-and post-conditions, i.e., a contract, that can be distributed to third-party developers. The framework ensures that if the components are compliant with their contracts, they can be safely integrated into the initial partial design without additional rework. As a result, FIDDle supports an iterative design process and guarantees correctness of the system at any step of development. We evaluated the effectiveness of FIDDle in supporting an iterative and incremental development of components using the K9 Mars Rover example developed at NASA Ames. This can be considered as an initial, yet substantive, validation of the approach in a realistic setting. We also assessed the scalability of FIDDle by comparing its efficiency with the classical model checkers implemented within the LTSA toolset. Results show that FIDDle scales as well as classical model checking as the number of the states of the components under development and their environments grow.

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“…To support explorative design, verification should be possible also on incomplete (partial) formal models. It is also necessary to provide techniques to formally verify models in face of their evolution [22,35].…”

Section: Supporting Dependable Evolutionmentioning

confidence: 99%

Formal Methods and Agile Development: Towards a Happy Marriage

Ghezzi

2018

The Essence of Software Engineering

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Change is connatural to software: no other human artifact shares this characteristic. Its immaterial nature and lack of physical constraints make it perfectly malleable: any change is in principle possible. Through simple textual operations, software engineers can add, delete, or modify functionalities offered by the software and improve its qualities (e.g., its performance). Technically, both the functional and the non-functional properties may be changed. The ability to provide extremely powerful functionalities in a highly flexible and changeable manner has been the key factor that leads to the current software-dominated world. Change, however, does not come for free. Despite the apparent simplicity of change operations, it is hard to ensure that changes achieve the desired goals. Change operations operate at a very low level (code level), while the requests for change are dictated by higher level goals, such as adding new functionalities, or speeding up execution, or improving usability. Making sure that changes achieve the new goals, while preserving satisfaction of other unchanged goals, is very often extremely hard. This is the reason why software developers often restrain changes. Change has been a concern since the 1970s, leading to the research work by Parnas [31-34], Belady and Lehman [6, 27], among others, and the recognition of "software maintenance" as a key concern. Traditional software development processes were mainly structured in a phased, rigidly planned manner, ideally intended to lead to robust processes that would eliminate the need for reconsidering and changing previous design decisions.

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Supporting incremental behaviour model elaboration

Cited by 12 publications

References 41 publications

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

Integrating Topological Proofs with Model Checking to Instrument Iterative Design

A verification-driven framework for iterative design of controllers

Formal Methods and Agile Development: Towards a Happy Marriage

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