Gotowe bibliografie tematyczne / Software verification

Gotowa bibliografia na temat „Software verification”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 25 maja 2024

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Artykuły w czasopismach na temat "Software verification"

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Kwiatkowska, Marta. "From software verification to ‘everyware’ verification". Computer Science - Research and Development 28, nr 4 (7.09.2013): 295–310. http://dx.doi.org/10.1007/s00450-013-0249-1.

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Goerigk, Wolfgang. "Mechanical Software Verification". Electronic Notes in Theoretical Computer Science 58, nr 2 (listopad 2001): 117–37. http://dx.doi.org/10.1016/s1571-0661(04)00282-8.

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Filliâtre, Jean-Christophe. "Deductive software verification". International Journal on Software Tools for Technology Transfer 13, nr 5 (20.08.2011): 397–403. http://dx.doi.org/10.1007/s10009-011-0211-0.

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Dobrescu, Mihai, i Katerina Argyraki. "Software dataplane verification". Communications of the ACM 58, nr 11 (23.10.2015): 113–21. http://dx.doi.org/10.1145/2823400.

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V. Gayetri Devi, S., C. Nalini i N. Kumar. "An efficient software verification using multi-layered software verification tool". International Journal of Engineering & Technology 7, nr 2.21 (20.04.2018): 454. http://dx.doi.org/10.14419/ijet.v7i2.21.12465.

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Rapid advancements in Software Verification and Validation have been critical in the wide development of tools and techniques to identify potential Concurrent bugs and hence verify the software correctness. A concurrent program has multiple processes and shared objects. Each process is a sequential program and they use the shared objects for communication for completion of a task. The primary objective of this survey is retrospective review of different tools and methods used for the verification of real-time concurrent software. This paper describes the proposed tool ‘F-JAVA’ for multithreaded Java codebases in contrast with existing ‘FRAMA-C’ platform, which is dedicated to real-time concurrent C software analysis. The proposed system is comprised of three layers, namely Programming rules generation stage, Verification stage with Particle Swarm Optimization (PSO) algorithm, and Performance measurement stage. It aims to address some of the challenges in the verification process such as larger programs, long execution times, and false alarms or bugs, and platform independent code verification
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Büchner, Frank. "Software Unit Verification of Medical Software". New Electronics 54, nr 3 (23.02.2021): 22–23. http://dx.doi.org/10.12968/s0047-9624(22)60332-8.

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Esbel, Ousama, i Ng Ah Ngan Mike Christian. "Hardware/Software Verification Process through Cloud Computing". Lecture Notes on Software Engineering 4, nr 2 (maj 2016): 123–28. http://dx.doi.org/10.7763/lnse.2016.v4.236.

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Korablin, Y. P., i A. A. Shipov. "Questions of verification in distributed software systems". Contemporary problems of social work 1, nr 2 (30.06.2015): 102–6. http://dx.doi.org/10.17922/2412-5466-2015-1-2-102-106.

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Huisman, Marieke. "Verification of Concurrent Software". Electronic Proceedings in Theoretical Computer Science 261 (29.11.2017): 2. http://dx.doi.org/10.4204/eptcs.261.2.

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Abdulla, Parosh Aziz, i K. Rustan M. Leino. "Tools for software verification". International Journal on Software Tools for Technology Transfer 15, nr 2 (3.03.2013): 85–88. http://dx.doi.org/10.1007/s10009-013-0270-5.

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Rozprawy doktorskie na temat "Software verification"

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Wang, Xuan. "Verification of Digital Controller Verifications". BYU ScholarsArchive, 2005. https://scholarsarchive.byu.edu/etd/681.

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This thesis presents an analysis framework to verify the stablility property of a closed-loop control system with a software controller implementation. The usual approach to verifying stability for software uses experiments which are costly and can be dangerous. More recently, mathematical models of software have been proposed which can be used to reason about the correctness of controllers. However, these mathematical models ignore computational details that may be important in verification. We propose a method to determine the instability of a closed-loop system with a software controller implementation under l^2 inputs using simulation. This method avoids the cost of experimentation and the loss of precision inherent in mathematical modeling. The method uses the small gain theorem to compute a lower bound on the 2-induced norm of the uncertainty in the software implementation; if the lower bound is greater than 1/(2-induced norm of G), where G is the feedback system consisting of the mathematical model of the plant and the mathematical model of the controller, the closed-loop system is unsafe in a certain sense. The resulting method can not determine if the closed-loop system is stable, but can only suggest instability.
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Kattenbelt, Mark Alex. "Automated quantitative software verification". Thesis, University of Oxford, 2010. http://ora.ox.ac.uk/objects/uuid:62430df4-7fdf-4c4f-b3cd-97ba8912c9f5.

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Many software systems exhibit probabilistic behaviour, either added explicitly, to improve performance or to break symmetry, or implicitly, through interaction with unreliable networks or faulty hardware. When employed in safety-critical applications, it is important to rigorously analyse the behaviour of these systems. This can be done with a formal verification technique called model checking, which establishes properties of systems by algorithmically considering all execution scenarios. In the presence of probabilistic behaviour, we consider quantitative properties such as "the worst-case probability that the airbag fails to deploy within 10ms", instead of qualitative properties such as "the airbag eventually deploys". Although many model checking techniques exist to verify qualitative properties of software, quantitative model checking techniques typically focus on manually derived models of systems and cannot directly verify software. In this thesis, we present two quantitative model checking techniques for probabilistic software. The first is a quantitative adaptation of a successful model checking technique called counter-example guided abstraction refinement which uses stochastic two-player games as abstractions of probabilistic software. We show how to achieve abstraction and refinement in a probabilistic setting and investigate theoretical extensions of stochastic two-player game abstractions. Our second technique instruments probabilistic software in such a way that existing, non-probabilistic software verification methods can be used to compute bounds on quantitative properties of the original, uninstrumented software. Our techniques are the first to target real, compilable software in a probabilistic setting. We present an experimental evaluation of both approaches on a large range of case studies and evaluate several extensions and heuristics. We demonstrate that, with our methods, we can successfully compute quantitative properties of real network clients comprising approximately 1,000 lines of complex ANSI-C code — the verification of such software is far beyond the capabilities of existing quantitative model checking techniques.
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Taylor, Ramsay G. "Verification of hardware dependent software". Thesis, University of Sheffield, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.575744.

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Many good processes exist for ensuring the integrity of software systems, Some are analysis processes that seek to confirm that cer- tain properties hold for the system, and these rely on the ability to infer a correct model of the behaviour of the software, To ensure that such inference is possible many high-integrity systems are writ- ten in "safe" language subsets that restrict the program to constructs whose behaviour is sufficiently abstract and well defined that it can be determined independent of the execution environment. This nec- essarily prevents any assumptions about the system hardware. but consequently makes it impossible to use these techniques on software that must interact with the hardware. such as device drivers. This thesis addresses this shortcoming by taking the opposite approach: if the analyst accepts absolute hardware dependence - that the analysis will only be valid for a particular target system: the hardware that the driver is intended to control -- then the specifica- tion of the system can be used to infer the behaviour of the software that interacts with it, An analysis process is developed that operates on disassembled executable files and formal system specifications to produce CSP-OZ formal models of the software's behaviour, This analysis process is implemented in a prototype called Spurinna. that is then used in conjunction with the verification tools Z2SAL, the SAL suite, and IsabelleHOL. to demonstrate the verification of prop- erties of the software.
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Jobredeaux, Romain J. "Formal verification of control software". Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53841.

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In a context of heightened requirements for safety-critical embedded systems and ever-increasing costs of verification and validation, this research proposes to advance the state of formal analysis for control software. Formal methods are a field of computer science that uses mathematical techniques and formalisms to rigorously analyze the behavior of programs. This research develops a framework and tools to express and prove high level properties of control law implementations. One goal is to bridge the gap between control theory and computer science. An annotation language is extended with symbols and axioms to describe control-related concepts at the code level. Libraries of theorems, along with their proofs, are developed to enable an interactive proof assistant to verify control-related properties. Through integration in a prototype tool, the process of verification is made automatic, and applied to several example systems.In a context of heightened requirements for safety-critical embedded systems and ever-increasing costs of verification and validation, this research proposes to advance the state of formal analysis for control software. Formal methods are a field of computer science that uses mathematical techniques and formalisms to rigorously analyze the behavior of programs. This research develops a framework and tools to express and prove high level properties of control law implementations. One goal is to bridge the gap between control theory and computer science. An annotation language is extended with symbols and axioms to describe control-related concepts at the code level. Libraries of theorems, along with their proofs, are developed to enable an interactive proof assistant to verify control-related properties. Through integration in a prototype tool, the process of verification is made automatic, and applied to several example systems.
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Kirschenbaum, Jason P. "Investigations in Automating Software Verification". The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1306862918.

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Ferro, Sara <1996&gt. "Software Verification of PLC programs". Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/17637.

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Programmable Logic Controllers (PLC) play an important role in Industrial Control Systems, as they manage the actions of physical tools by collecting data from input devices and sending commands to output devices. In this thesis, we introduce a formal framework for software verification of robustness of PLC programs. In particular, we identify external vulnerabilities based on dynamic user interaction, we define the semantics of Structured Control Language (SCL) and the semantics of Timed Automata (TA), we provide a set of transformation rules to transform a program written in SCL to a Timed Automaton, and we show their correctness with respect to the corresponding semantics. By applying these transformation rules, we can apply Model Checking tools (namely UPPAAL) to verify robustness properties of the PLC source code.
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Olliaro, Martina <1991&gt. "String analysis for software verification". Doctoral thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/18470.

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This thesis aims to investigate string manipulation with security implications in different programming languages and to improve the state-of-the-art by applying the abstract interpretation theory to string analysis. Erroneous string manipulation is a challenging problem in software verification and, in fact, it is one of the major cause of program vulnerabilities that can be exploited by malicious users, leading to severe consequences for the affected systems. By string analysis we mean statically computing the set of string values that are possibly assigned to a variable. Like for other analysis issues, this is undecidable. Thus a certain degree of approximation is necessary in order to find evidence of bugs and vulnerabilities in string manipulating code. We take advantage of the Abstract Interpretation theory, i.e., a powerful mathematical theory that enables us to define and prove the soundness of approximations. The five main contributions of this thesis are: We introduce a new sophisticated abstract domain for C strings. The way the domain (called M-String) is conceived allows it to be tailored for specific verification tasks (e.g., detection of buffer overflows). We describe the concrete and the abstract semantics of basic string operations and prove their soundness formally. Furthermore, we provide an executable implementation of abstract operations. Using a tool that automatically lifts existing programs into the M-String domain along with an explicit-state model checker, we evaluate the accuracy of the proposed domain experimentally on real-case test programs. We combine abstract domains resulting from the reduced product between string shape abstraction and string content abstraction, in order to improve the ability to detect inconsistent states leading to program errors without a major impact with respect to efficiency. In particular, the combinations involve some string abstract domains introduced in the literature with the segmentation domain that we instantiate for string analysis. Completeness, in Abstract Interpretation, ensures that the analysis does not lose information with respect to the property of interest. We provide a systematic and constructive approach for generating the completion of string domains for dynamic languages, and we apply it to the refinement of existing string abstractions. Indeed, for dynamic languages, lack of string analysis completeness is a key security issue, as poorly managed string manipulation code may easily lead to significant security flaws. We also provide an effective procedure to measure the precision improvement obtained when lifting the analysis to complete domains. Almost all the existing string abstract domains tracks information of single variables in a program (e.g., if a string contains a certain character), without inspecting their relationship with other values, causing the loss of relevant knowledge about their possible values. Thus, we introduce a generic framework that allows to formalize relational string abstract domains based on ordering relationship, and we instantiate such a framework to several domains built upon different well-known string orders (e.g., substring relationships). We implemented the domain based on substring ordering, and we provide an experimental evaluation about its effectiveness on some case studies. We manipulate string values in the context of relational database watermarking. We propose a semantic-driven watermarking approach of relational textual databases, which marks multi-word textual attributes, exploiting the synonym substitution technique for text watermarking together with notions in semantic similarity analysis, and dealing with the semantic perturbations provoked by the watermark embedding. We show the effectiveness of our approach through an experimental evaluation. We also prove the resilience of our approach with respect to the random synonym substitution attack.
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Zucchelli, D. "Combination Methods for Software Verification". Doctoral thesis, Università degli Studi di Milano, 2008. http://hdl.handle.net/2434/45877.

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The thesis is devoted to the development of formal methods for software verification. Indeed, two are among the most widespread techniques that allow to rigorously specify the possible executions of a system and check whether it contains bugs. On the one hand, the correctness of a program can be guaranteed by showing the unsatisfiability of a formula modulo a theory which usually axiomatizes the involved datatypes; on the other hand, the model checking techniques are used to certify that every possible run of the system satisfies the desired properties. The contributions of the thesis are the following: First of all, we give a decidability result for the constraint satisfiability problem for interesting extensions of the theory of arrays. Secondly, along the lines of Manna and Pnueli, who have shown how a mixture of first-order logic and linear time temporal logic is sufficient to state the verification problems for the class of reactive systems, we draw on the recent literature about the combination of decision procedures to give decidability and undecidability results for the satisfiability problem for logics that allow to plug reasoning modulo first-order theories into a temporal setting. The results obtained in the case of linear flows of time are then generalized to the temporal and modal logics whose relativized satisfiability problem is decidable. The last contribution is the decidability of the model checking problem for linear flows of time under suitable hypothesis over the first-order theories involved. The proofs of the decidability results suggest that efficient Satisfiability Modulo Theories solvers might be successfully employed in the model checking of infinite-state systems.
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Domagoj, Babić. "Exploiting structure for scalable software verification". Thesis, University of British Columbia, 2008. http://hdl.handle.net/2429/1502.

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Software bugs are expensive. Recent estimates by the US National Institute of Standards and Technology claim that the cost of software bugs to the US economy alone is approximately 60 billion USD annually. As society becomes increasingly software-dependent, bugs also reduce our productivity and threaten our safety and security. Decreasing these direct and indirect costs represents a significant research challenge as well as an opportunity for businesses. Automatic software bug-finding and verification tools have a potential to completely revolutionize the software engineering industry by improving reliability and decreasing development costs. Since software analysis is in general undecidable, automatic tools have to use various abstractions to make the analysis computationally tractable. Abstraction is a double-edged sword: coarse abstractions, in general, yield easier verification, but also less precise results. This thesis focuses on exploiting the structure of software for abstracting away irrelevant behavior. Programmers tend to organize code into objects and functions, which effectively represent natural abstraction boundaries. Humans use such structural abstractions to simplify their mental models of software and for constructing informal explanations of why a piece of code should work. A natural question to ask is: How can automatic bug-finding tools exploit the same natural abstractions? This thesis offers possible answers. More specifically, I present three novel ways to exploit structure at three different steps of the software analysis process. First, I show how symbolic execution can preserve the data-flow dependencies of the original code while constructing compact symbolic representations of programs. Second, I propose structural abstraction, which exploits the structure preserved by the symbolic execution. Structural abstraction solves a long-standing open problem --- scalable interprocedural path- and context-sensitive program analysis. Finally, I present an automatic tuning approach that exploits the fine-grained structural properties of software (namely, data- and control-dependency) for faster property checking. This novel approach resulted in a 500-fold speedup over the best previous techniques. Automatic tuning not only redefined the limits of automatic software analysis tools, but also has already found its way into other domains (like model checking), demonstrating the generality and applicability of this idea.
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Hughes, Roger Brett. "Automated interactive software verification and synthesis". Thesis, Brunel University, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306741.

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Książki na temat "Software verification"

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Bloem, Roderick, Rayna Dimitrova, Chuchu Fan i Natasha Sharygina, red. Software Verification. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-95561-8.

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Christakis, Maria, Nadia Polikarpova, Parasara Sridhar Duggirala i Peter Schrammel, red. Software Verification. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63618-0.

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Abate, Alessandro, i Sylvie Boldo, red. Numerical Software Verification. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63501-9.

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Zamani, Majid, i Damien Zufferey, red. Numerical Software Verification. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28423-7.

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Bogomolov, Sergiy, Matthieu Martel i Pavithra Prabhakar, red. Numerical Software Verification. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54292-8.

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Stanley, William, i Janusz Laski. Software Verification and Analysis. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-240-5.

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Bérard, Béatrice, Michel Bidoit, Alain Finkel, François Laroussinie, Antoine Petit, Laure Petrucci, Philippe Schnoebelen i Pierre McKenzie. Systems and Software Verification. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04558-9.

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Arceri, Vincenzo, Agostino Cortesi, Pietro Ferrara i Martina Olliaro, red. Challenges of Software Verification. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9601-6.

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Petrinja, Etiel, Giancarlo Succi, Nabil El Ioini i Alberto Sillitti, red. Open Source Software: Quality Verification. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38928-3.

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Meyer, Bertrand, i Martin Nordio, red. Empirical Software Engineering and Verification. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25231-0.

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Części książek na temat "Software verification"

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Alagić, Suad. "Software Verification". W Software Engineering: Specification, Implementation, Verification, 139–70. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61518-9_6.

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Revesz, Peter. "Software Verification". W Texts in Computer Science, 685–99. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84996-095-3_26.

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Weik, Martin H. "software verification". W Computer Science and Communications Dictionary, 1611. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17667.

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Pocernich, Matthew. "Appendix: Verification Software". W Forecast Verification, 231–40. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781119960003.app1.

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Peled, Doron A. "Deductive Software Verification". W Texts in Computer Science, 179–213. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3540-6_7.

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Weik, Martin H. "automated software verification". W Computer Science and Communications Dictionary, 81. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_1068.

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Sanchez, Ernesto, Giovanni Squillero i Alberto Tonda. "Automatic Software Verification". W Intelligent Systems Reference Library, 17–30. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27467-1_3.

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Almeida, José Bacelar, Maria João Frade, Jorge Sousa Pinto i Simão Melo de Sousa. "Generating Verification Conditions". W Rigorous Software Development, 159–79. London: Springer London, 2011. http://dx.doi.org/10.1007/978-0-85729-018-2_6.

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Jha, Susmit. "Trust, Resilience and Interpretability of AI Models". W Numerical Software Verification, 3–25. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28423-7_1.

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Somenzi, Fabio, i Ashutosh Trivedi. "Reinforcement Learning and Formal Requirements". W Numerical Software Verification, 26–41. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-28423-7_2.

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Streszczenia konferencji na temat "Software verification"

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Silva, Nuno, i Rui Lopes. "Independent Test Verification: Consolidated Experience Report". W Simpósio Brasileiro de Qualidade de Software. Sociedade Brasileira de Computação - SBC, 2012. http://dx.doi.org/10.5753/sbqs.2012.15326.

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Independent verification and validation (IV&V) has been a key process for decades, and is highlighted in several international certification standards. One of the activities described in the “ESA ISVV Guide” is independent test verification (stated as Integration/Unit Test Procedures and Test Data Verification). This activity is commonly overlooked since customers do not really see the added value of checking thoroughly the validation team work. This article presents the consolidated results of a large set of independent test verifications, including the main difficulties, results obtained and advantages/disadvantages for the industry of these activities. This study will support customers in opting-in or opting-out for this task in future IVV contracts since we provide factual results from some real case studies.
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Malkis, Alexander, i Anindya Banerjee. "Verification of software barriers". W the 17th ACM SIGPLAN symposium. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2145816.2145871.

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Holzmann, Gerard J. "Economics of software verification". W the 2001 ACM SIGPLAN-SIGSOFT workshop. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/379605.379681.

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Baradarani, A., J. R. B. Taylor, F. Severin i R. Gr Maev. "Advanced fingerprint verification software". W SPIE Defense + Security, redaktor Edward M. Carapezza. SPIE, 2016. http://dx.doi.org/10.1117/12.2224244.

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Carter, Montgomery, Shaobo He, Jonathan Whitaker, Zvonimir Rakamarić i Michael Emmi. "SMACK software verification toolchain". W ICSE '16: 38th International Conference on Software Engineering. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2889160.2889163.

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Bucur, Doina, i Marta Z. Kwiatkowska. "Software verification for TinyOS". W the 9th ACM/IEEE International Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1791212.1791274.

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"Session details: Software verification". W SAC07: The 2007 ACM Symposium on Applied Computing, redaktorzy Lunjin Lu i Fausto Spoto. New York, NY, USA: ACM, 2007. http://dx.doi.org/10.1145/3246520.

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Spoto, Fausto. "Session details: Software verification". W SAC '08: The 2008 ACM Symposium on Applied Computing. New York, NY, USA: ACM, 2008. http://dx.doi.org/10.1145/3260537.

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Montangero, Carlo. "Session details: Verification". W ESEC/FSE01: European Software Engineering Conference 2001/ Foundations on Software Engineering 2001. New York, NY, USA: ACM, 2001. http://dx.doi.org/10.1145/3247726.

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Nguyen, Minh D., i Wolfgang Kunz. "Hardware/software formal co-verification using hardware verification techniques". W 2012 Fourth International Conference on Communications and Electronics (ICCE). IEEE, 2012. http://dx.doi.org/10.1109/cce.2012.6315951.

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Raporty organizacyjne na temat "Software verification"

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Strichman, Ofer. Software Regression Verification. Fort Belvoir, VA: Defense Technical Information Center, grudzień 2013. http://dx.doi.org/10.21236/ada594501.

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COMPUSEC INC SAN DIEGO CA. Secure Software Verification Tools. Fort Belvoir, VA: Defense Technical Information Center, luty 1987. http://dx.doi.org/10.21236/ada189731.

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Wallace, Dolores R., i Roger U. Fujii. Software verification and validation. Gaithersburg, MD: National Institute of Standards and Technology, 1989. http://dx.doi.org/10.6028/nist.sp.500-165.

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Davis, Nickolas, Taylor Berger, Arthur McDonald, Joey Ingram, James Foster i Katherine Sanchez. Software Verification Toolkit (SVT): Survey on Available Software Verification Tools and Future Direction. Office of Scientific and Technical Information (OSTI), sierpień 2022. http://dx.doi.org/10.2172/1884906.

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Hosmer, Chester. Feasibility of Software Patch Verification. Fort Belvoir, VA: Defense Technical Information Center, czerwiec 2004. http://dx.doi.org/10.21236/ada425345.

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Chen, Y., D. W. Engel, B. P. McGrail i K. S. Lessor. AREST-CT V1.0 software verification. Office of Scientific and Technical Information (OSTI), lipiec 1995. http://dx.doi.org/10.2172/105064.

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Olund, Thomas S. Software Verification and Validation Procedure. Office of Scientific and Technical Information (OSTI), wrzesień 2008. http://dx.doi.org/10.2172/1027706.

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Leyva, Nha. Uncertainty Analysis and Software Verification. Office of Scientific and Technical Information (OSTI), lipiec 2021. http://dx.doi.org/10.2172/1813900.

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Riemenschneider, R. A., Theodore A. Linden, Karen Morgan i William Vrotney. Verification and Validation of AI Software. Fort Belvoir, VA: Defense Technical Information Center, maj 1992. http://dx.doi.org/10.21236/ada254601.

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Kalinina, Elena Arkadievna. TSL-CALVIN Software Verification and Validation. Office of Scientific and Technical Information (OSTI), październik 2014. http://dx.doi.org/10.2172/1163120.

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