Automated Termination Analysis of Java Bytecode by Term Rewriting

We present an automated approach to prove termination of Java Bytecode (JBC) programs by automatically transforming them to term rewrite systems (TRSs). In this way, the numerous techniques and tools developed for TRS termination can now be used for imperative object-oriented languages like Java, which can be compiled into JBC

Potency of transgenic effectors for neurogenetic manipulation in Drosophila larvae

Genetic manipulations of neuronal activity are a cornerstone of studies aimed to identify the functional impact of defined neurons for animal behavior. With its small nervous system, rapid life cycle, and genetic amenability, the fruit fly Drosophila melanogaster provides an attractive model system to study neuronal circuit function. In the past two decades, a large repertoire of elegant genetic tools has been developed to manipulate and study neural circuits in the fruit fly. Current techniques allow genetic ablation, constitutive silencing, or hyperactivation of neuronal activity and also include conditional thermogenetic or optogenetic activation or inhibition. As for all genetic techniques, the choice of the proper transgenic tool is essential for behavioral studies. Potency and impact of effectors may vary in distinct neuron types or distinct types of behavior. We here systematically test genetic effectors for their potency to alter the behavior of Drosophila larvae, using two distinct behavioral paradigms: general locomotor activity and directed, visually guided navigation. Our results show largely similar but not equal effects with different effector lines in both assays. Interestingly, differences in the magnitude of induced behavioral alterations between different effector lines remain largely consistent between the two behavioral assays. The observed potencies of the effector lines in aminergic and cholinergic neurons assessed here may help researchers to choose the best-suited genetic tools to dissect neuronal networks underlying the behavior of larval fruit flies

ObjSim: Lightweight Automatic Patch Prioritization via Object Similarity

In the context of test case based automatic program repair (APR), patches that pass all the test cases but fail to fix the bug are called overfitted patches. Currently, patches generated by APR tools get inspected manually by the users to find and adopt genuine fixes. Being a laborious activity hindering widespread adoption of APR, automatic identification of overfitted patches has lately been the topic of active research. This paper presents engineering details of ObjSim: a fully automatic, lightweight similarity-based patch prioritization tool for JVM-based languages. The tool works by comparing the system state at the exit point(s) of patched method before and after patching and prioritizing patches that result in state that is more similar to that of original, unpatched version on passing tests while less similar on failing ones. Our experiments with patches generated by the recent APR tool PraPR for fixable bugs from Defects4J v1.4.0 show that ObjSim prioritizes 16.67% more genuine fixes in top-1 place. A demo video of the tool is located at https://bit.ly/2K8gnYV.Comment: Proceedings of the 29th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA '20), July 18--22, 2020, Virtual Event, US

Synthesizing Systems with Optimal Average-Case Behavior for Ratio Objectives

We show how to automatically construct a system that satisfies a given logical specification and has an optimal average behavior with respect to a specification with ratio costs. When synthesizing a system from a logical specification, it is often the case that several different systems satisfy the specification. In this case, it is usually not easy for the user to state formally which system she prefers. Prior work proposed to rank the correct systems by adding a quantitative aspect to the specification. A desired preference relation can be expressed with (i) a quantitative language, which is a function assigning a value to every possible behavior of a system, and (ii) an environment model defining the desired optimization criteria of the system, e.g., worst-case or average-case optimal. In this paper, we show how to synthesize a system that is optimal for (i) a quantitative language given by an automaton with a ratio cost function, and (ii) an environment model given by a labeled Markov decision process. The objective of the system is to minimize the expected (ratio) costs. The solution is based on a reduction to Markov Decision Processes with ratio cost functions which do not require that the costs in the denominator are strictly positive. We find an optimal strategy for these using a fractional linear program.Comment: In Proceedings iWIGP 2011, arXiv:1102.374

Mapping and assessment of forest ecosystems and their services - Applications and guidance for decision making in the framework of MAES

The aim of this report is to illustrate by means of a series of case studies the implementation of mapping and assessment of forest ecosystem services in different contexts and geographical levels. Methodological aspects, data issues, approaches, limitations, gaps and further steps for improvement are analysed for providing good practices and decision making guidance. The EU initiative on Mapping and Assessment of the state of Ecosystems and their Services (MAES), with the support of all Member States, contributes to improve the knowledge on ecosystem services. MAES is one of the building-block initiatives supporting the EU Biodiversity Strategy to 2020.JRC.H.3-Forest Resources and Climat

Takeaways from the Nordic Food Waste Summit 2023

For two days, ministers, entrepreneurs, activists, and royalty stood side by side at the Nordic Food Waste Summit 2023 in the common battle against wasted resources − through political panel discussions, visionary keynotes, coffee-fueled networking, and concrete business cases. This brief provides a summary of some of the discussions and conclusions that arose from the summit and the action needed ahead. In the Nordic countries approximately 3.6 million tons of food are wasted annually. If food waste were a country, it would be the third biggest greenhouse gas emitter in the world. Reducing food loss and waste are key aspects to create sustainable food systems for the health of our environment, climate, and people. The Nordic Food Waste Summit 2023 made it abundantly clear that a stronger Nordic collaboration is one of the most important steppingstones towards a more resource-efficient and waste-free regional food system

Vérification et synthèse quantitative

This thesis contributes to the theoretical study and application of quantitative verification and synthesis. We first study strategies that optimize the ratio of two rewards in MDPs. The goal is the synthesis of efficient controllers in probabilistic environments. We prove that deterministic and memoryless strategies are sufficient. Based on these results we suggest 3 algorithms to treat explicitly encoded models. Our evaluation of these algorithms shows that one of these is clearly faster than the others. To extend its scope, we propose and implement a symbolic variant based on binary decision diagrams, and show that it cope with millions of states. Second, we study the problem of program repair from a quantitative perspective. This leads to a reformulation of program repair with the requirement that only faulty runs of the program be changed. We study the limitations of this approach and show how we can relax the new requirement. We devise and implement an algorithm to automatically find repairs, and show that it improves the changes made to programs.Third, we study a novel approach to a quantitative verification and synthesis framework. In this, verification and synthesis work in tandem to analyze the quality of a controller with respect to, e.g., robustness against modeling errors. We also include the possibility to approximate the Pareto curve that emerges from combining the model with multiple rewards. This allows us to both study the trade-offs inherent in the system and choose a configuration to our liking. We apply our framework to several case studies. The major case study is concerned with the currently proposed next generation airborne collision avoidance system (ACAS X). We use our framework to help analyze the design space of the system and to validate the controller as currently under investigation by the FAA. In particular, we contribute analysis via PCTL and stochastic model checking to add to the confidence in the controller.Cette thèse contribue à l'étude théorique et a l'application de la vérification et de la synthèse quantitative. Nous étudions les stratégies qui optimisent la fraction de deux récompenses des MDPs. L'objectif est la synthèse de régulateurs efficaces dans des environnements probabilistes. Premièrement nous montrons que les stratégies déterministes et sans mémoire sont suffisants. Sur la base de ces résultats, nous proposons trois algorithmes pour traiter des modèles explicitement encodées. Notre évaluation de ces algorithmes montre que l'un de ces derniers est plus rapide que les autres. Par la suite nous proposons et mettons en place une variante symbolique basé sur les diagrammes de décision binaire.Deuxièmement, nous étudions le problème de réparation des programmes d'un point de vue quantitatif. Cela conduit à une reformulation de la réparation d'un log: que seules les exécutions fautives du programme soient modifiées. Nous étudions les limites de cette approche et montrons comment nous pouvons assouplir cette nouvelle exigence. Nous concevons et mettons en œuvre un algorithme pour trouver automatiquement des réparations, et montrons qu'il améliore les modifications apportées aux programmes. Troisièmement, nous étudions une nouvelle approche au framework pour la vérification et synthèse quantitative. La vérification et la synthèse fonctionnent en tandem pour analyser la qualité d'un contrôleur en ce qui concerne, par exemple , de robustesse contre des erreurs de modélisation. Nous considérons également la possibilité d'approximer la courbure de Pareto, qui appataît de la combinaison du modèle avec de multiples récompenses. Cela nous permet à la fois d'étudier les compromis inhérents au système et de choisir une configuration adéquate. Nous appliquons notre framework aux plusieurs études de cas. La majorité de l'étude de cas est concernée par un système anti-collision embarqué (ACAS X). Nous utilisons notre framework pour aider à analyser l'espace de conception du système et de valider le contrôleur en cours d'investigation par la FAA. En particulier, nous contribuons l'analyse par PCTL et stochastic model checking

Program repair without regret

We present a new and flexible approach to repair reactive programs with respect to a specification. The specification is given in linear-temporal logic. Like in previous approaches, we aim for a repaired program that satisfies the specification and is syntactically close to the faulty program. The novelty of our approach is that it produces a program that is also semantically close to the original program by enforcing that a subset of the original traces is preserved. Intuitively, the faulty program is considered to be a part of the specification, which enables us to synthesize meaningful repairs, even for incomplete specifications. Our approach is based on synthesizing a program with a set of behaviors that stay within a lower and an upper bound. We provide an algorithm to decide if a program is repairable with respect to our new notion, and synthesize a repair if one exists. We analyze several ways to choose the set of traces to leave intact and show the boundaries they impose on repairability. We also discuss alternative notions based on reward models to obtain repair systems that behave similar to the original system. We have evaluated the approach on several examples