Constraint-based BMC: a backjumping strategy

Collavizza, Hélène; Vinh, Nguyen Le; Ponsini, Olivier; Rueher, Michel; Rollet, Antoine

doi:10.1007/s10009-012-0258-6

Cited by 7 publications

(8 citation statements)

References 32 publications

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“…Constraint based BMC is a BMC approach that uses constraints for modeling the program and its specification, and constraint solving for checking if the program conforms its specification [8,9]. BMC uses a bound b to unfold loops: they are replaced with conditional statements of depth b.…”

Section: Constraint Based Bmcmentioning

confidence: 99%

LocFaults

Bekkouche

Collavizza

Rueher

2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

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We introduce in this paper LocFaults, a new flow-driven and constraint-based approach for error localization. The input is a faulty program for which a counter-example and a postcondition are provided. To identify helpful information for error location, we generate a constraint system for the paths of the control flow graph for which at most k conditional statements may be erroneous. Then, we calculate Minimal Correction Sets (MCS) of bounded size for each of these paths. The removal of one of these sets of constraints yields a maximal satisfiable subset, in other words, a maximal subset of constraints satisfying the post condition. To compute the MCS, we extend the algorithm proposed by Liffiton and Sakallah [21] in order to handle programs with numerical statements more efficiently. The main advantage of this flow-driven approach is that the computed sets of suspicious instructions are small, each of them being associated with an identified path. Moreover, the constraintprogramming based framework of LocFaults allows mixing Boolean and numerical constraints in an efficient and straightforward way. Preliminary experiments are quite encouraging. * This work was partially supported by ANR VAC-SIM (ANR-11-INSE-0004), ANR AEOLUS (ANR-10-SEGI-0013), and OSEO ISI PAJERO projects.

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Section: Constraint Based Bmcmentioning

confidence: 99%

LocFaults

Bekkouche

Collavizza

Rueher

2015

Proceedings of the 30th Annual ACM Symposium on Applied Computing

Self Cite

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“…Rather than backtracking to the last instantiated variable chronologically, backjmping (BJ) [18] goes to the deepest past variable in conflict with the current variable. In conflict-directed backjumping (CBJ) [19], each variable has its conflicting set consisting of the past variables which failed consistency checks with its current instantiation.…”

Section: Backtracking Searchmentioning

confidence: 99%

A hybrid backtracking algorithm for automatic test data generation

et al. 2017

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Original scientific paper As a fundamental issue in software testing, automatic test data generation is of crucial importance, which is essentially a constraint satisfaction problem and solved by search algorithms. In our previous research, branch and bound was proposed as our constraint solver and the look-ahead methods were elaborated. Based on interval arithmetic and symbolic execution, this paper focuses on the look-back or backtracking method, which is the hybridization of forward checking and conflict-directed backjumping, with the aim of improving the efficiency of backtracking in the search procedure. The closures of variables are used to facilitate the localization of the conflicts which cause dead ends. Empirical experiments prove the effectiveness of the proposed hybrid backtracking method and its applicability in engineering. Keywords: automatic test data generation; backtracking; closure; conflict-directed backjumping; forward checking Hibridni unatražni algoritam za automatsko generiranje podataka za ispitivanjeIzvorni znanstveni članak Kao osnovno pitanje u ispitivanju softvera, automatsko generiranje podataka za ispitivanje je od najveće važnosti, što je u biti problem zadovoljavanja ograničenja, a rješava se algoritmima pretraživanja. U našem prethodnom istraživanju za rješenje ograničenja predložena je metoda grananja i ograničavanja, a elaborirane su unaprijedne metode. Zasnovan na intervalnom aritmetičkom i simboličkom izvršenju, ovaj je rad usredotočen na unatražnu metodu, a to je povezivanje unaprijednog provjeravanja i unatražnog ispitivanja usmjerenog konflikta, u cilju poboljšanja učinkovitosti unatražnog praćenja u postupku traženja. Zatvaranja varijabli se koriste kako bi se olakšalo lociranje nesuglasica koje dovode do neriješenih rezultata (dead ends). Empirijski eksperimenti dokazuju učinkovitost predložene hibridne unatražne metode i njenu primjenljivost u inženjerstvu.Ključne riječi: automatsko generiranje podataka za ispitivanje; unaprijedno provjeravanje; unatražno praćenje; unatražno skakanje na osnovu konflikta; zatvaranje

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“…This model, taken from [9], represents a flasher manager manufactured by Geensoft/Dasssault Systems and is responsible for driving the behavior of the flashing lights of a car. The Simulink model of this device is pictured in Figure 12.…”

Section: A Considered Modelmentioning

confidence: 99%

“…In [9], the authors considered 4 properties of the flasher manager component. For this paper, we will consider the fourth one.…”

Section: A) Direction Changementioning

confidence: 99%

“…We will consider a bounded version of the property, by setting a maximum number of cycles during which the lights shall not remain lit. In [9], the authors checked the property for bounds of 10, 50, 100 and more (up to 1,600 cycles). They found one counterexample for every bound, but did not discuss the underlying behavior (their focus was on benchmarking model-checking algorithms).…”

Section: A) Direction Changementioning

confidence: 99%

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Show Me New Counterexamples: A Path-Based Approach

Castillos

Waeselynck

Wiels

2015

2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST)

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We consider lightweight usage of model-checking for the debugging of Simulink models. A problem is that modelcheckers typically return only one counterexample, which may slow down the debugging process. We propose an approach and a tool to produce several counterexamples, exemplifying different property violation patterns for a given version of the design. The approach uses data collected during the replay of the counterexamples to synthesize queries for the model-checker, so that it finds counterexamples that activate new paths. The approach is applied to an academic example and an industrial model from the automotive domain.

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Constraint-based BMC: a backjumping strategy

Cited by 7 publications

References 32 publications

LocFaults

LocFaults

A hybrid backtracking algorithm for automatic test data generation

Show Me New Counterexamples: A Path-Based Approach

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