3,516 research outputs found
An Instantiation-Based Approach for Solving Quantified Linear Arithmetic
This paper presents a framework to derive instantiation-based decision
procedures for satisfiability of quantified formulas in first-order theories,
including its correctness, implementation, and evaluation. Using this framework
we derive decision procedures for linear real arithmetic (LRA) and linear
integer arithmetic (LIA) formulas with one quantifier alternation. Our
procedure can be integrated into the solving architecture used by typical SMT
solvers. Experimental results on standardized benchmarks from model checking,
static analysis, and synthesis show that our implementation of the procedure in
the SMT solver CVC4 outperforms existing tools for quantified linear
arithmetic
"We are always after that balance":managing innovation in the new digital media industry
The pressure to innovate is growing as technology cycles change more rapidly. Organisations need to balance exploration and exploitation effectively if they are to heed the innovation imperative. Organisational ambidexterity is proposed as a means to achieve such balance with structural or contextual ambidexterity as possible choices. Yet how organisations become ambidextrous is an as yet underresearched area, and different industry sectors may pose different innovation challenges. Using the case study method, this paper examines how a computer games company responds to an industry-specific innovation challenge and how it endeavours to balance exploration and exploitation. The findings suggest that ambidexterity is difficult to achieve, and is fraught with organisational tensions which might eventually jeopardise the innovation potential of a company. The paper suggests that more qualitative research is needed to further our understanding of innovation challenges, innovation management and organisational ambidexterity
A Survey of Symbolic Execution Techniques
Many security and software testing applications require checking whether
certain properties of a program hold for any possible usage scenario. For
instance, a tool for identifying software vulnerabilities may need to rule out
the existence of any backdoor to bypass a program's authentication. One
approach would be to test the program using different, possibly random inputs.
As the backdoor may only be hit for very specific program workloads, automated
exploration of the space of possible inputs is of the essence. Symbolic
execution provides an elegant solution to the problem, by systematically
exploring many possible execution paths at the same time without necessarily
requiring concrete inputs. Rather than taking on fully specified input values,
the technique abstractly represents them as symbols, resorting to constraint
solvers to construct actual instances that would cause property violations.
Symbolic execution has been incubated in dozens of tools developed over the
last four decades, leading to major practical breakthroughs in a number of
prominent software reliability applications. The goal of this survey is to
provide an overview of the main ideas, challenges, and solutions developed in
the area, distilling them for a broad audience.
The present survey has been accepted for publication at ACM Computing
Surveys. If you are considering citing this survey, we would appreciate if you
could use the following BibTeX entry: http://goo.gl/Hf5FvcComment: This is the authors pre-print copy. If you are considering citing
this survey, we would appreciate if you could use the following BibTeX entry:
http://goo.gl/Hf5Fv
Autonomy Operating System for UAVs: Pilot-in-a-Box
The Autonomy Operating System (AOS) is an open flight software platform with Artificial Intelligence for smart UAVs. It is built to be extendable with new apps, similar to smartphones, to enable an expanding set of missions and capabilities. AOS has as its foundations NASAs core flight executive and core flight software (cFEcFS). Pilot-in-a-Box (PIB) is an expanding collection of interacting AOS apps that provide the knowledge and intelligence onboard a UAV to safely and autonomously fly in the National Air Space, eventually without a remote human ground crew. Longer-term, the goal of PIB is to provide the capability for pilotless air vehicles such as air taxis that will be key for new transportation concepts such as mobility-on-demand. PIB provides the procedural knowledge, situational awareness, and anticipatory planning (thinking ahead of the plane) that comprises pilot competencies. These competencies together with a natural language interface will enable Pilot-in-a-Box to dialogue directly with Air Traffic Management from takeoff through landing. This paper describes the overall AOS architecture, Artificial Intelligence reasoning engines, Pilot-in-a-box competencies, and selected experimental flight tests to date
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