A technique for detecting wait-notify deadlocks in Java

Deadlock analysis of object-oriented programs that dynamically create threads and objects is complex, because these programs may have an infinite number of states. In this thesis, I analyze the correctness of wait - notify patterns (e.g. deadlock freedom) by using a newly introduced technique that consists in an analysis model that is a basic concurrent language with a formal semantic. I detect deadlocks by associating a Petri Net graph to each process of the input program. This model allows to check if a deadlock occur by analysing the reachability tree. The technique presented is a basic step of a more complex and complete project, since in my work I only consider programs with one object

Achromobacter spp. in Cystic Fibrosis Patients: A Genomic-Based Approach to Unravel Microbe-Host Adaptation

Bacteria belonging to the genus Achromobacter are widely distributed in natural environments and have been recognized as emerging nosocomial pathogens for their contribution to a wide range of human infections. Achromobacter spp. can establish chronic infections associated with inflammation, produce biofilm, resist common disinfectants, readily acquire antibiotic resistance and outcompete resident microbiota. In particular, cystic fibrosis (CF) patients with lung disease are the most frequently colonized and infected by Achromobacter species usually developing persistent respiratory tract infections. In the last five years the number of publications regarding these pathogens has doubled in comparison to the preceding five-year period and their whole genome sequencing data availability has seen a steep increase, underlining both the growing research interest for these microorganisms as well as their emergence in the clinical setting. Nonetheless, many clinical aspects and pathogenic mechanisms still remain to be elucidated. The main focus of this thesis has been to unravel underlying key processes and to investigate the adaptive mechanisms exploited by these microorganisms during lung infection in CF patients. This has been pursued by analysing both genomic and phenotypic data of 103 Achromobacter spp. clinical isolates from 40 CF patients followed at the CF centres in Verona (Italy), Rome (Italy), and Copenhagen (Denmark). The work presented in this thesis provides new knowledge on the onset of Achromobacter spp. infections and their adaptation to the CF lung environment. With further genomic and phenotypic studies it will be possible to translate these results into the clinical setting, leading to better predictions of the infection course and improvement of treatment strategies to the benefit of CF patients

A Formal Analysis of the Bitcoin Protocol

none2noWe study Nakamoto’s Bitcoin protocol that implements a distributed ledger on peer-to-peer asynchronous networks. In particular, we define a principled formal model of key participants - the miners - as stochastic processes and describe the whole system as a parallel composition of miners. We therefore compute the probability that ledgers turn into a state with more severe inconsistencies, e.g. with longer forks, under the assumptions that messages are not lost and nodes are not hostile. We also study how the presence of hostile nodes mining blocks in wrong positions impacts on the consistency of the ledgers. Our theoretical results agree with the simulations performed on a probabilistic model checker that we extended with dynamic datatypes in order to have a faithful description of miners' behaviour.openAdele Veschetti, Cosimo LaneveAdele Veschetti, Cosimo Lanev

SmartML: Towards a Modeling Language for Smart Contracts

Smart contracts codify real-world transactions and automatically execute the terms of the contract when predefined conditions are met. This paper proposes SmartML, a modeling language for smart contracts that is platform independent and easy to comprehend. We detail its formal semantics and type system with a focus on its role in addressing security vulnerabilities. We show along a case study, how SmartML contributes to the prevention of reentrancy attacks, illustrating its efficacy in reinforcing the reliability and security of smart contracts within decentralized systems

The interplay between microbiota and human complex traits

Microorganisms have been one of the most influential drivers propelling some of the greatest environmental and evolutionary changes in the landscape and biology of the entire planet [...]

The BioVRPi project: a valuable and sustainable alternative for genomic analysis

Since 2012, the Raspberry Pi Foundation has started developing pocket-sized and low-cost devices, originally meant to teach computer science in developing Countries. Its growing interest and constant improvement led Raspberry Pi devices to find different applications and to suit the needs of various research areas. In the previous years, different researchers already reported applications of Raspberry Pi devices in bioinformatics, such as basic train- ing and proteomics. In the beginning of 2021, we gave birth to BioVRPi, a project which aims to develop and offer a low-cost and stable bioinformatic environment for students and re- searchers involved in the genomics and transcriptomics fields. We evaluated performances and software compatibilities of different scenarios, focusing on Genome-Wide Association Studies for complex traits in Homo sapiens, transcriptomic analyses on RNA-seq data from Strongyloides stercoralis samples and alignment of small organisms, such as SARS-CoV-2 (virus), Escherichia Coli (bacterium) and Caenorhabditis elegans (nematode). Results from both the bioinformatic and benchmarking analyses showed that Raspberry Pi devices are capable of accomplishing different bioinformatic tasks in terms of results and performances. Moreover, they proved to be a valuable low-cost and sustainable alternative, in accordance with the United Nation 2030 Agenda, to answer the needs and the challenges of the current socio-economic situation

Towards pocket-sized genomic analyses: cross-platform benchmark of multi-organism genomic data indexing and alignment

The current socio-economic situation as well as international objectives set by the United Nation (2030 Sustainable Agenda) underline the urgency of low-cost and environmental-friendly computational alternatives. Moreover, in recent years the bioinformatic community has shown renewed interest for Raspberry Pi (RPi) application in teaching and research projects. In the context of the BioVRPi project - which aims to develop and offer a low-cost, stable and tested bioinformatic environment - we propose an exploratory cross-platform benchmarking of multi-organism genomic analyses. The benchmark of indexing and alignment processes was carried out on the following devices: RPi 4 (Raspberry Pi OS 04-04-2022) RAM 8GB HDD storage, laptop (MacOS Big Sur v11.2.3) Intel Core i5 2GHz quad-core processor RAM 16GB SSD, and desktop (Ubuntu 20.04.4 LTS) Intel Core i7 3GHz octa-core processor RAM 32GB HDD storage. Performance assessment was evaluated on SARS-CoV-2 virus, Escherichia coli and Caenorhabditis elegans genome sequences (respective RefSeq accessions: GCF_009858895.2, GCF_000005845.2, GCF_000002985.6) since they present different degrees of genomic complexity: virus, bacterium, and nematode. To minimize variability and possible biases due to sequencing technologies used, sample reads were generated in silico from their respective reference genomes using ART Illumina v2.5.8 with the following parameters: read length 150, paired end, coverage 30X, mean fragment length 200, standard deviation 10, HiSeqX v2.5 TruSeq built-in profile. Indexing and alignment were performed with 3 alignment tools: BWA v0.7.17-r1188, Bowtie2 v2.4.5, and Minimap2 v2.17, using default parameters and scaling from 1 up to 4 threads. Benchmarking was evaluated using Hyperfine v1.13.0 with a warmup step of 3 simulations and 10 runs for each process. We performed a cross-platform benchmark of multi-organism genomic indexing and short reads alignment to evaluate RPi as a viable alternative to common bioinformatic devices. To assess its performance, we tested some of the most widely used alignment tools on SARS-CoV-2, E. coli and C. elegans genomic data (respective genome sizes: 29.9Kbp, 4.6Mbp, 100.3Mbp). The computational times for indexing and alignment are reported in Table 1. As regards indexing, we observed comparable runtimes among RPi and other platforms using BWA and Bowtie2 for SARS-CoV-2 and E. coli, whereas Minimap2 indexing showed an increase of one order of magnitude in runtimes for RPi. Nonetheless, Minimap2 showed the fastest runtimes for indexing overall. In addition, we found an increase of one order of magnitude in RPi runtimes for C. elegans for all considered tools, even though differences in runtimes across platforms showed to be stable across organisms. As regards the alignment process, we observed consistency in runtimes differences across all organisms and tools. Overall, Minimap2 performances proved to be the fastest whereas Bowtie2 displayed poor performances across all platforms, exacerbating its inefficiency on RPi. Even though BWA seems to work more efficiently on RPi than on desktop for SARS-COV-2 data, desktop and laptop showed better performances on more complex organisms as expected. Benchmarking analyses considered multi-threading up to 4 threads, the maximum available on RPi. As regards indexing on Bowtie2, multi-threading proved to be effective for C. elegans data, showing no improvement in runtimes for SARS-CoV-2 and E. coli. Conversely, alignment showed the best performances using multi-threading as expected. In conclusion, RPi showed promising results, proved to be a viable low-cost and environmental-friendly alternative to perform genomic data analysis on different organisms and turned out to be particularly efficient for microorganisms. Further advances and tools optimization for RPi ARM architecture will lead to a greater scalability for complex organisms and will be carried out by the BioVRPi project in future exploratory analyses

Resilience of Hybrid Casper under varying values of parameters

Hybrid Casper is the new Ethereum blockchain protocol that uses both Proof of Work and Proof of Stake to reach a consensus between nodes. Here, we analyse the protocol using PRISM+, an extension of the probabilistic model checker PRISM with primitives for expressing blockchain data types. First, we extend PRISM+ to include data types and operations for modelling and analysing Proof of Stake-based consensus protocols. Then, we model Hybrid Casper in PRISM+ as a parallel composition of stochastic processes, thus precisely describing the behaviour of the protocol and highlighting its corner cases. PRISM+ is therefore used to rapidly and automatically analyse the resilience of Hybrid Casper when tuning, up or down, several basic parameters of the protocol, such as the rates of creating blocks, and the strategies for determining penalties. Finally, we study the robustness of Hybrid Casper to two well known attacks: the Eclipse attack and the majority attack

A formal analysis of blockchain consensus

In this thesis, we analyse these protocols using PRISM+, our extension of the probabilistic model checker PRISM with blockchain types and operations upon them. This allows us to model the behaviour of key participants in the protocols and describe the protocols as a parallel composition of PRISM+ processes. Through our analysis of the Bitcoin model, we are able to understand how forks (where different nodes have different versions of the blockchain) occur and how they depend on specific parameters of the protocol, such as the difficulty of the cryptopuzzle and network communication delays. Our results corroborate the statement that considering confirmed the transactions in blocks at depth larger than 5 is reasonable because the majority of miners have consistent blockchains up-to that depth with probability of almost 1. We also study the behaviour of the Bitcoin network with churn miners (nodes that leave and rejoin the network) and with different topologies (linear topology, ring topology, tree topology and fully connected topology). PRISM+ is therefore used to analyse the resilience of Hybrid Casper when changing various basic parameters of the protocol, such as block creation rates and penalty determination strategies. We also study the robustness of Hybrid Casper against two known attacks: the Eclipse attack (where an attacker controls a significant portion of the network's nodes and can prevent other nodes from receiving new transactions) and the majority attack (where an attacker controls a majority of the network's nodes and can manipulate the blockchain to their advantage)