Can you Trust your Data?

Forfattere

  • Peter Ørbæk

DOI:

https://doi.org/10.7146/brics.v2i24.19926

Resumé

A new program analysis is presented, and two compile time methods for this analysis are given. The analysis attempts to answer the question: “Given some trustworthy and some untrustworthy input, can we trust the value of a given variable after execution of some code”. The analyses are based on an abstract interpretation framework and a constraint generation
framework, respectively. The analyses are proved safe with respect to an instrumented semantics. We explicitly deal with a language with pointers and possible aliasing problems.
The constraint based analysis is related directly to the abstract interpretation and therefore indirectly to the instrumented semantics.

Downloads

Publiceret

1995-01-24

Citation/Eksport

Ørbæk, P. (1995). Can you Trust your Data?. BRICS Report Series, 2(24). https://doi.org/10.7146/brics.v2i24.19926

Nummer

Nr. 24 (1995): RS-24 Can you Trust your Data?

Sektion

Artikler

Licens

Authors who publish with this journal agree to the following terms:

    1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

    1. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.

  1. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).