Automatic Software Verification

2012 ◽  
pp. 17-30 ◽  
Author(s):  
Ernesto Sanchez ◽  
Giovanni Squillero ◽  
Alberto Tonda
Keyword(s):  
Software Verification ◽  
Automatic Software

Automatic software verification for robotics

2008 ◽  
Vol 21 (4) ◽  
pp. 263-264 ◽  
Author(s):  
Jacopo Mantovani
Keyword(s):  
Software Verification ◽  
Automatic Software

scholarly journals Software Verification: 10th Comparative Evaluation (SV-COMP 2021)

2021 ◽  
pp. 401-422
Author(s):  
Dirk Beyer
Keyword(s):  
Comparative Evaluation ◽  
Software Verification ◽  
Verification Task ◽  
C Programs ◽  
Current State ◽  
Strong Focus ◽  
Java Programs ◽  
Automatic Software ◽  
Fully Automatic ◽  
Verification Systems

AbstractSV-COMP 2021 is the 10th edition of the Competition on Software Verification (SV-COMP), which is an annual comparative evaluation of fully automatic software verifiers for C and Java programs. The competition provides a snapshot of the current state of the art in the area, and has a strong focus on reproducibility of its results. The competition was based on 15 201 verification tasks for C programs and 473 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). SV-COMP 2021 had 30 participating verification systems from 27 teams from 11 countries.

scholarly journals Advances in Automatic Software Verification: SV-COMP 2020

2020 ◽  
pp. 347-367 ◽  
Author(s):  
Dirk Beyer
Keyword(s):  
Software Verification ◽  
State Of The Art ◽  
Verification Task ◽  
C Programs ◽  
Current State ◽  
Strong Focus ◽  
Java Programs ◽  
Automatic Software ◽  
Fully Automatic ◽  
Verification Systems

Abstract This report describes the 2020 Competition on Software Verification (SV-COMP), the 9$$^{\text {th}}$$ edition of a series of comparative evaluations of fully automatic software verifiers for C and Java programs. The competition provides a snapshot of the current state of the art in the area, and has a strong focus on replicability of its results. The competition was based on 11 052 verification tasks for C programs and 416 verification tasks for Java programs. Each verification task consisted of a program and a property (reachability, memory safety, overflows, termination). SV-COMP 2020 had 28 participating verification systems from 11 countries.

Synthesizing Conjunctive & Disjunctive Linear Invariants by K-means++ and SVM

2020 ◽  
Vol 17 (6) ◽  
pp. 847-856
Author(s):  
Shengbing Ren ◽  
Xiang Zhang
Keyword(s):  
Software Verification ◽  
State Of The Art ◽  
Positive Sample ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Hoare Logic ◽  
Excellent Performance ◽  
Automated Software ◽  
Inductive Invariants ◽  
Linear Invariants

The problem of synthesizing adequate inductive invariants lies at the heart of automated software verification. The state-of-the-art machine learning algorithms for synthesizing invariants have gradually shown its excellent performance. However, synthesizing disjunctive invariants is a difficult task. In this paper, we propose a method k++ Support Vector Machine (SVM) integrating k-means++ and SVM to synthesize conjunctive and disjunctive invariants. At first, given a program, we start with executing the program to collect program states. Next, k++SVM adopts k-means++ to cluster the positive samples and then applies SVM to distinguish each positive sample cluster from all negative samples to synthesize the candidate invariants. Finally, a set of theories founded on Hoare logic are adopted to check whether the candidate invariants are true invariants. If the candidate invariants fail the check, we should sample more states and repeat our algorithm. The experimental results show that k++SVM is compatible with the algorithms for Intersection Of Half-space (IOH) and more efficient than the tool of Interproc. Furthermore, it is shown that our method can synthesize conjunctive and disjunctive invariants automatically

scholarly journals Retinal vascular fractal dimensions and their association with macrovascular cardiac disease.

2021 ◽  
Author(s):  
Sebastian Dinesen ◽  
Pia Søndergaard Jensen ◽  
Maria Bloksgaard ◽  
Søren Leer Blindbæk ◽  
Jo G.R. De Mey ◽  
...  
Keyword(s):  
Confidence Interval ◽  
Cardiac Disease ◽  
Artery Bypass ◽  
Fractal Dimensions ◽  
Macrovascular Disease ◽  
Control Group ◽  
Vascular Structure ◽  
Non Invasive ◽  
Automatic Software ◽  
Multivariable Regression

Introduction As the only part of the human vasculature, retina is available for direct, non-invasive inspection. Retinal vascular fractal dimension (DF) is a method to measure the structure of the retinal vascular tree, with higher non-integer values between 1 and 2 representing a more complex and dense retinal vasculature. Retinal vascular structure has been associated with a variety of systemic diseases and this study examined the association of DF and macrovascular cardiac disease in a case-control design. Methods Retinal fundus photos were captured with Topcon TRC-50X in 38 persons that had coronary artery bypass grafting (CABG, cases) and 37 cardiovascular healthy controls. The semi-automatic software VAMPIRE was used to measure retinal DF. Results Patients with CABG had lower DF of the retinal main venular vessels compared to the control group (1.15 vs. 1.18, p=0.01). In a multivariable regression model adjusted for gender and age, eyes in the fourth quartile with higher DF were less likely to have CABG compared to patients in the first (OR, 7.20; 95% confidence interval, 1.63 to 31.86; p=0.009) and second quartile (OR, 8.25; 95% confidence interval, 1.70 to 40.01; p=0.009). Conclusions This study demonstrates that lower complexity of main venular vessels associates with higher risk of having CABG. The research supports the hypothesis that the retinal vascular structure can be used to assess non-ocular macrovascular disease.

scholarly journals SAT modulo discrete event simulation applied to railway design capacity analysis

2021 ◽  
Author(s):  
Bjørnar Luteberget ◽  
Koen Claessen ◽  
Christian Johansen ◽  
Martin Steffen
Keyword(s):  
Discrete Event Simulation ◽  
Construction Projects ◽  
Software Verification ◽  
Ad Hoc ◽  
Discrete Event ◽  
Capacity Analysis ◽  
Railway Network ◽  
Event Simulation ◽  
Design Engineers ◽  
Railway Capacity

AbstractThis paper proposes a new method of combining SAT with discrete event simulation. This new integration proved useful for designing a solver for capacity analysis in early phase railway construction design. Railway capacity is complex to define and analyze, and existing tools and methods used in practice require comprehensive models of the railway network and its timetables. Design engineers working within the limited scope of construction projects report that only ad-hoc, experience-based methods of capacity analysis are available to them. Designs often have subtle capacity pitfalls which are discovered too late, only when network-wide timetables are made—there is a mismatch between the scope of construction projects and the scope of capacity analysis, as currently practiced. We suggest a language for capacity specifications suited for construction projects, expressing properties such as running time, train frequency, overtaking and crossing. Such specifications can be used as contracts in the interface between construction projects and network-wide capacity analysis. We show how these properties can be verified fully automatically by building a special-purpose solver which splits the problem into two: an abstracted SAT-based dispatch planning, and a continuous-domain dynamics with timing constraints evaluated using discrete event simulation. The two components communicate in a CEGAR loop (counterexample-guided abstraction refinement). This architecture is beneficial because it clearly distinguishes the combinatorial choices on the one hand from continuous calculations on the other, so that the simulation can be extended by relevant details as needed. We describe how loops in the infrastructure can be handled to eliminate repeating dispatch plans, and use case studies based on data from existing infrastructure and ongoing construction projects to show that our method is fast enough at relevant scales to provide agile verification in a design setting. Similar SAT modulo discrete event simulation combinations could also be useful elsewhere where one or both of these methods are already applicable such as in bioinformatics or hardware/software verification.

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