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Constructing a safety case for automatically generated code from formal program verification

Constructing a safety case for automatically generated code from formal program verification
Constructing a safety case for automatically generated code from formal program verification
Formal methods can in principle provide the highest levels of assurance of code safety by providing formal proofs as explicit evidence for the assurance claims. However, the proofs are often complex and difficult to relate to the code, in particular if it has been generated automatically. They may also be based on assumptions and reasoning principles that are not justified. This causes concerns about the trustworthiness of the proofs and thus the assurance claims. Here we present an approach to systematically construct safety cases from information collected during a formal verification of the code, in particular from the construction of the logical annotations necessary for a formal, Hoare-style safety certification. Our approach combines a generic argument that is instantiated with respect to the certified safety property (i.e., safety claims) with a detailed, program-specific argument that can be derived systematically because its structure directly follows the course the annotation construction takes through the code. The resulting safety cases make explicit the formal and informal reasoning principles, and reveal the top-level assumptions and external dependencies that must be taken into account. However, the evidence still comes from the formal safety proofs. Our approach is independent of the given safety property and program, and consequently also independent of the underlying code generator. Here, we illustrate it for the AutoFilter system developed at NASA Ames.
249-262
Springer-Verlag Berlin Heidelberg
Basir, N.
10c027b2-6fdd-46db-ab74-83d526522558
Denney, E.
ea98c398-f905-4e8f-8a1c-0a47b49e0abd
Fischer, B.
0c9575e6-d099-47f1-b3a2-2dbc93c53d18
Harrison, Michael Douglas
Sujan, Mark-Alexander
Basir, N.
10c027b2-6fdd-46db-ab74-83d526522558
Denney, E.
ea98c398-f905-4e8f-8a1c-0a47b49e0abd
Fischer, B.
0c9575e6-d099-47f1-b3a2-2dbc93c53d18
Harrison, Michael Douglas
Sujan, Mark-Alexander

Basir, N., Denney, E. and Fischer, B. (2008) Constructing a safety case for automatically generated code from formal program verification. Harrison, Michael Douglas and Sujan, Mark-Alexander (eds.) In Computer Safety, Reliability, and Security. : 27th International Conference, SAFECOMP 2008 Newcastle upon Tyne, UK, September 22-25, 2008 Proceedings. vol. 5219, Springer-Verlag Berlin Heidelberg. pp. 249-262 .

Record type: Conference or Workshop Item (Paper)

Abstract

Formal methods can in principle provide the highest levels of assurance of code safety by providing formal proofs as explicit evidence for the assurance claims. However, the proofs are often complex and difficult to relate to the code, in particular if it has been generated automatically. They may also be based on assumptions and reasoning principles that are not justified. This causes concerns about the trustworthiness of the proofs and thus the assurance claims. Here we present an approach to systematically construct safety cases from information collected during a formal verification of the code, in particular from the construction of the logical annotations necessary for a formal, Hoare-style safety certification. Our approach combines a generic argument that is instantiated with respect to the certified safety property (i.e., safety claims) with a detailed, program-specific argument that can be derived systematically because its structure directly follows the course the annotation construction takes through the code. The resulting safety cases make explicit the formal and informal reasoning principles, and reveal the top-level assumptions and external dependencies that must be taken into account. However, the evidence still comes from the formal safety proofs. Our approach is independent of the given safety property and program, and consequently also independent of the underlying code generator. Here, we illustrate it for the AutoFilter system developed at NASA Ames.

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More information

Published date: 2008
Organisations: Electronic & Software Systems

Identifiers

Local EPrints ID: 269071
URI: https://eprints.soton.ac.uk/id/eprint/269071
PURE UUID: cc203ba2-cc41-4788-bb8f-8c26e40dc327

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Date deposited: 21 Apr 2010 07:46
Last modified: 06 Nov 2018 17:30

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