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Conference object . 2018
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https://dx.doi.org/10.48550/ar...
Article . 2018
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Conference object . 2018
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Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Authors: De Angelis E; Fioravanti F; Palacios A; Pettorossi A; Proietti M;

Bounded Symbolic Execution for Runtime Error Detection of Erlang Programs

Abstract

Dynamically typed languages, like Erlang, allow developers to quickly write programs without explicitly providing any type information on expressions or function definitions. However, this feature makes those languages less reliable than statically typed languages, where many runtime errors can be detected at compile time. In this paper, we present a preliminary work on a tool that, by using the well-known techniques of metaprogramming and symbolic execution, can be used to perform bounded verification of Erlang programs. In particular, by using Constraint Logic Programming, we develop an interpreter that, given an Erlang program and a symbolic input for that program, returns answer constraints that represent sets of concrete data for which the Erlang program generates a runtime error.

In Proceedings HCVS 2018, arXiv:1809.04554

Keywords

FOS: Computer and information sciences, Computer Science - Logic in Computer Science, Computer Science - Programming Languages, D.2.5, D.2.4, QA75.5-76.95, Erlang, Logic in Computer Science (cs.LO), Electronic computers. Computer science, QA1-939, Computer programming languages; Errors; Logic programming; Model checking, Bounded Verification, D.2.4;D.2.5;F.3.1, F.3.1, Mathematics, Programming Languages (cs.PL)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
2
Average
Average
Average
Green
gold