Development of Agent-Based Simulation Models for Software Evolution

Software ist ein Bestandteil des alltäglichen Lebens für uns geworden. Dies ist auch mit zunehmenden Anforderungen an die Anpassungsfähigkeit an sich schnell ändernde Umgebungen verbunden. Dieser evolutionäre Prozess der Software wird von einem dem Software Engineering zugehörigen Forschungsbereich, der Softwareevolution, untersucht. Die Änderungen an einer Software über die Zeit werden durch die Arbeit der Entwickler verursacht. Aus diesem Grund stellt das Entwicklerverhalten einen zentralen Bestandteil dar, wenn man die Evolution eines Softwareprojekts analysieren möchte. Für die Analyse realer Projekte steht eine Vielzahl von Open Source Projekten frei zur Verfügung. Für die Simulation von Softwareprojekten benutzen wir Multiagentensysteme, da wir damit das Verhalten der Entwickler detailliert beschrieben können. In dieser Dissertation entwickeln wir mehrere, aufeinander aufbauende, agentenbasierte Modelle, die unterschiedliche Aspekte der Software Evolution abdecken. Wir beginnen mit einem einfachen Modell ohne Abhängigkeiten zwischen den Agenten, mit dem man allein durch das Entwicklerverhalten das Wachstum eines realen Projekts simulativ reproduzieren kann. Darauffolgende Modelle wurden um weitere Agenten, zum Beispiel unterschiedliche Entwickler-Typen und Fehler, sowie Abhängigkeiten zwischen den Agenten ergänzt. Mit diesen erweiterten Modellen lassen sich unterschiedliche Fragestellungen betreffend Software Evolution simulativ beantworten. Eine dieser Fragen beantwortet zum Beispiel was mit der Software bezüglich ihrer Qualität passiert, wenn der Hauptentwickler das Projekt plötzlich verlässt. Das komplexeste Modell ist in der Lage Software Refactorings zu simulieren und nutzt dazu Graph Transformationen. Die Simulation erzeugt als Ausgabe einen Graphen, der die Software repräsentiert. Als Repräsentant der Software dient der Change-Coupling-Graph, der für die Simulation von Refactorings erweitert wird. Dieser Graph wird in dieser Arbeit als \emph{Softwaregraph} bezeichnet. Um die verschiedenen Modelle zu parametrisieren haben wir unterschiedliche Mining-Werkzeuge entwickelt. Diese Werkzeuge ermöglichen es uns ein Modell mit projektspezifischen Parametern zu instanziieren, ein Modell mit einem Snapshot des analysierten Projektes zu instanziieren oder Transformationsregeln zu parametrisieren, die für die Modellierung von Refactorings benötigt werden. Die Ergebnisse aus drei Fallstudien zeigen unter anderem, dass unser Ansatz agentenbasierte Simulation für die Vorhersage der Evolution von Software Projekten eine geeignete Wahl ist. Des Weiteren konnten wir zeigen, dass mit einer geeigneten Parameterwahl unterschiedliche Wachstumstrends der realen Software simulativ reproduzierbar sind. Die besten Ergebnisse für den simulierten Softwaregraphen erhalten wir, wenn wir die Simulation nach einer initialen Phase mit einem Snapshot der realen Software starten. Die Refactorings betreffend konnten wir zeigen, dass das Modell basierend auf Graph Transformationen anwendbar ist und dass das simulierte Wachstum sich damit leicht verbessern lässt.Software has become a part of everyday life for us. This is also associated with increasing requirements for adaptability to rapidly changing environments. This evolutionary process of software is being studied by a software engineering related research area, called software evolution. The changes to a software over time are caused by the work of the developers. For this reason, the developer contribution behavior is central for analyzing the evolution of a software project. For the analysis of real projects, a variety of open source projects is freely available. For the simulation of software projects, we use multiagent systems because this allows us to describe the behavior of the developers in detail. In this thesis, we develop several successive agent-based models that cover different aspects of software evolution. We start with a simple model with no dependencies between the agents that can simulative reproduce the growth of a real project solely based on the developer’s contribution behavior. Subsequent models were supplemented by additional agents, such as different developer types and bugs, as well as dependencies between the agents. These advanced models can then be used to answer different questions concerning software evolution simulative. For example, one of these questions answers what happens to the software in terms of quality when the core developer suddenly leaves the project. The most complex model can simulate software refactorings based on graph transformations. The simulation output is a graph which represents the software. The representative of the software is the change coupling graph, which is extended for the simulation of refactorings. In this thesis, this graph is denoted as \emph{software graph}. To parameterize these models, we have developed different mining tools. These tools allow us to instantiate a model with project-specific parameters, to instantiate a model with a snapshot of the analyzed project, or to parameterize the transformation rules required to model refactorings. The results of three case studies show, among other things, that our approach to use agent-based simulation is an appropriate choice for predicting the evolution of software projects. Furthermore, we were able to show that different growth trends of the real software can be reproduced simulative with a suitable selection of simulation parameters. The best results for the simulated software graph are obtained when we start the simulation after an initial phase with a snapshot of real software. Regarding refactorings, we were able to show that the model based on graph transformations is applicable and that it can slightly improve the simulated growth

Galba: genome annotation with miniprot and AUGUSTUS

Abstract Background The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. Results Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein-to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. Conclusions Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms

Assessment of current methane emission quantification techniques for natural gas midstream applications

International audienceAbstract. Methane emissions from natural gas systems are increasingly scrutinized, and accurate reporting requires quantification of site- and source-level measurement. We evaluate the performance of 10 available state-of-the-art CH4 emission quantification approaches against a blind controlled-release experiment at an inerted natural gas compressor station in 2021. The experiment consisted of 17 blind 2 h releases at a single exhaust point or multiple simultaneous ones. The controlled releases covered a range of methane flow rates from 0.01 to 50 kg h−1. Measurement platforms included aircraft, drones, trucks, vans, ground-based stations, and handheld systems. Herewith, we compare their respective strengths, weaknesses, and potential complementarity depending on the emission rates and atmospheric conditions. Most systems were able to quantify the releases within an order of magnitude. The level of errors from the different systems was not significantly influenced by release rates larger than 0.1 kg h−1, with much poorer results for the 0.01 kg h−1 release. It was found that handheld optical gas imaging (OGI) cameras underestimated the emissions. In contrast, the “site-level” systems, relying on atmospheric dispersion, tended to overestimate the emission rates. We assess the dependence of emission quantification performance on key parameters such as wind speed, deployment constraints, and measurement duration. At the low wind speeds encountered (below 2 m s−1), the experiments did not reveal a significant dependence on wind speed. The ability to quantify individual sources degraded during multiple-source releases. Compliance with the Oil and Gas Methane Partnership's (OGMP 2.0) highest level of reporting may require a combination of the specific advantages of each measurement technique and will depend on reconciliation approaches. Self-reported uncertainties were either not available or were based on the standard deviation in a series of independent realizations or fixed values from expert judgment or theoretical considerations. For most systems, the overall relative errors estimated in this study are higher than self-reported uncertainties

Effect of anakinra versus usual care in adults in hospital with COVID-19 and mild-to-moderate pneumonia (CORIMUNO-ANA-1): a randomised controlled trial

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Effect of Tocilizumab vs Usual Care in Adults Hospitalized With COVID-19 and Moderate or Severe Pneumonia

International audienceImportance Severe pneumonia with hyperinflammation and elevated interleukin-6 is a common presentation of coronavirus disease 2019 (COVID-19).Objective To determine whether tocilizumab (TCZ) improves outcomes of patients hospitalized with moderate-to-severe COVID-19 pneumonia.Design, Setting, and Particpants This cohort-embedded, investigator-initiated, multicenter, open-label, bayesian randomized clinical trial investigating patients with COVID-19 and moderate or severe pneumonia requiring at least 3 L/min of oxygen but without ventilation or admission to the intensive care unit was conducted between March 31, 2020, to April 18, 2020, with follow-up through 28 days. Patients were recruited from 9 university hospitals in France. Analyses were performed on an intention-to-treat basis with no correction for multiplicity for secondary outcomes.Interventions Patients were randomly assigned to receive TCZ, 8 mg/kg, intravenously plus usual care on day 1 and on day 3 if clinically indicated (TCZ group) or to receive usual care alone (UC group). Usual care included antibiotic agents, antiviral agents, corticosteroids, vasopressor support, and anticoagulants.Main Outcomes and Measures Primary outcomes were scores higher than 5 on the World Health Organization 10-point Clinical Progression Scale (WHO-CPS) on day 4 and survival without need of ventilation (including noninvasive ventilation) at day 14. Secondary outcomes were clinical status assessed with the WHO-CPS scores at day 7 and day 14, overall survival, time to discharge, time to oxygen supply independency, biological factors such as C-reactive protein level, and adverse events.Results Of 131 patients, 64 patients were randomly assigned to the TCZ group and 67 to UC group; 1 patient in the TCZ group withdrew consent and was not included in the analysis. Of the 130 patients, 42 were women (32%), and median (interquartile range) age was 64 (57.1-74.3) years. In the TCZ group, 12 patients had a WHO-CPS score greater than 5 at day 4 vs 19 in the UC group (median posterior absolute risk difference [ARD] −9.0%; 90% credible interval [CrI], −21.0 to 3.1), with a posterior probability of negative ARD of 89.0% not achieving the 95% predefined efficacy threshold. At day 14, 12% (95% CI −28% to 4%) fewer patients needed noninvasive ventilation (NIV) or mechanical ventilation (MV) or died in the TCZ group than in the UC group (24% vs 36%, median posterior hazard ratio [HR] 0.58; 90% CrI, 0.33-1.00), with a posterior probability of HR less than 1 of 95.0%, achieving the predefined efficacy threshold. The HR for MV or death was 0.58 (90% CrI, 0.30 to 1.09). At day 28, 7 patients had died in the TCZ group and 8 in the UC group (adjusted HR, 0.92; 95% CI 0.33-2.53). Serious adverse events occurred in 20 (32%) patients in the TCZ group and 29 (43%) in the UC group (P = .21).Conclusions and Relevance In this randomized clinical trial of patients with COVID-19 and pneumonia requiring oxygen support but not admitted to the intensive care unit, TCZ did not reduce WHO-CPS scores lower than 5 at day 4 but might have reduced the risk of NIV, MV, or death by day 14. No difference on day 28 mortality was found. Further studies are necessary for confirming these preliminary results.Trial Registration ClinicalTrials.gov Identifier: NCT0433180

Sarilumab in adults hospitalised with moderate-to-severe COVID-19 pneumonia (CORIMUNO-SARI-1): An open-label randomised controlled trial

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