Falsification of Cyber-Physical Systems with Robustness-Guided Black-Box Checking

For exhaustive formal verification, industrial-scale cyber-physical systems (CPSs) are often too large and complex, and lightweight alternatives (e.g., monitoring and testing) have attracted the attention of both industrial practitioners and academic researchers. Falsification is one popular testing method of CPSs utilizing stochastic optimization. In state-of-the-art falsification methods, the result of the previous falsification trials is discarded, and we always try to falsify without any prior knowledge. To concisely memorize such prior information on the CPS model and exploit it, we employ Black-box checking (BBC), which is a combination of automata learning and model checking. Moreover, we enhance BBC using the robust semantics of STL formulas, which is the essential gadget in falsification. Our experiment results suggest that our robustness-guided BBC outperforms a state-of-the-art falsification tool.Comment: Accepted to HSCC 202

ViSpec: A graphical tool for elicitation of MTL requirements

One of the main barriers preventing widespread use of formal methods is the elicitation of formal specifications. Formal specifications facilitate the testing and verification process for safety critical robotic systems. However, handling the intricacies of formal languages is difficult and requires a high level of expertise in formal logics that many system developers do not have. In this work, we present a graphical tool designed for the development and visualization of formal specifications by people that do not have training in formal logic. The tool enables users to develop specifications using a graphical formalism which is then automatically translated to Metric Temporal Logic (MTL). In order to evaluate the effectiveness of our tool, we have also designed and conducted a usability study with cohorts from the academic student community and industry. Our results indicate that both groups were able to define formal requirements with high levels of accuracy. Finally, we present applications of our tool for defining specifications for operation of robotic surgery and autonomous quadcopter safe operation.Comment: Technical report for the paper to be published in the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems held in Hamburg, Germany. Includes 10 pages and 19 figure

LIMITATIONS OF PROCEDURAL FAIRNESS: THE CONSTITUTIONAL COMPLAINT AS AN EFFECTIVE REMEDY IN PRACTICE AND LAW

Even though the conduct of fair proceedings is very important, it does not necessarily lead to a fair outcome of the given proceedings. Thus, fair proceedings must be complemented by a fair substantive outcome in order to render basic rights practical and effective. The reason for such a shortcoming of procedural fairness might be manifold, but it essentially boils down to the mechanical application of the law, excessive formalism in the application and interpretation of the law, and a failure to go beyond mere appearances and assess the realities of the situation complained of. In this paper, I expound on the role of the constitutional complaint as an effective remedy pertinent to individuals who have an arguable claim regarding a violation of their substantive rights guaranteed by the ECHR and the Constitution alike. This paper analyses a ruling of the Constitutional Court of Kosovo where it found a violation of the right to privacy and family life and the right to an effective remedy, notwithstanding the fair conduct of the proceedings. I will also show the impact of the relevant case law of the European Court on the approach and rationale of the Constitutional Court

Towards the mainstream? The AfD as a case study

The radical right-wing party, the Alternative für Deutschland, caused a political tremor in 2017 German election by changing the political landscape significantly while becoming the third largest party in the Bundestag. Also, with most of the studies that asses AfD’s development being published while the party was starting to transform itself, the Euro crisis has lost its urgency, and given that party has been going through internal struggles for a while between ‘liberals’ and ‘extremists’ leads to the question on whether the AfD has shifted towards the mainstream? This dissertation works with the definition of ‘mainstreaming’ provided by Akkerman et al. (2016) and assess the party change along four key dimensions: 1) changes with respect to radical positions on core issues; 2) changes from a niche party to a party that focused on socioeconomic issues; 3) changes in the anti-establishment profile; and 4) changes regarding the party reputation. The research strategy adopted to this dissertation is the qualitative case study and consisted of a review of relevant literature the topic, coupled with the collection and analysis of a comprehensive range source of data. The findings from this research show that there is no sign that the AfD is shifting towards the mainstream; on the contrary, the party is tending to radicalize along first three dimensions while showing signs of mainstreaming on the fourth dimension to avoid possible juridical actions.https://www.ester.ee/record=b5193795*es

Latent deep sequential learning of behavioural sequences

The growing use of asynchronous online education (MOOCs and e-courses) in recent years has resulted in increased economic and scientific productivity, which has worsened during the coronavirus epidemic. The widespread usage of OLEs has increased enrolment, including previously excluded students, resulting in a far higher dropout rate than in conventional classrooms. Dropouts are a significant problem, especially considering the rising proliferation of online courses, from individual MOOCs to whole academic programmes due to the pandemic. Increased efficiency in dropout prevention techniques is vital for institutions, students, and faculty members and must be prioritised. In response to the resurgence of interest in the student dropout prediction (SDP) issue, there has been a significant rise in contributions to the literature on this topic. An in-depth review of the current state of the art literature on SDP is provided, with a special emphasis on Machine Learning prediction approaches; however, this is not the only focus of the thesis. We propose a complete hierarchical categorisation of the current literature that correlates to the process of design decisions in the SDP, and we demonstrate how it may be implemented. In order to enable comparative analysis, we develop a formal notation for universally defining the multiple dropout models examined by scholars in the area, including online degrees and their attributes. We look at several other important factors that have received less attention in the literature, such as evaluation metrics, acquired data, and privacy concerns. We emphasise deep sequential machine learning approaches and are considered to be one of the most successful solutions available in this field of study. Most importantly, we present a novel technique - namely GRU-AE - for tackling the SDP problem using hidden spatial information and time-related data from student trajectories. Our method is capable of dealing with data imbalances and time-series sparsity challenges. The proposed technique outperforms current methods in various situations, including the complex scenario of full-length courses (such as online degrees). This situation was thought to be less common before the outbreak, but it is now deemed important. Finally, we extend our findings to different contexts with a similar characterisation (temporal sequences of behavioural labels). Specifically, we show that our technique can be used in real-world circumstances where the unbalanced nature of the data can be mitigated by using class balancement technique (i.e. ADASYN), e.g., survival prediction in critical care telehealth systems where balancement technique alleviates the problem of inter-activity reliance and sparsity, resulting in an overall improvement in performance

LIMITATIONS OF PROCEDURAL FAIRNESS: THE CONSTITUTIONAL COMPLAINT AS AN EFFECTIVE REMEDY IN PRACTICE AND LAW

Even though the conduct of fair proceedings is very important, it does not necessarily lead to a fair outcome of the given proceedings. Thus, fair proceedings must be complemented by a fair substantive outcome in order to render basic rights practical and effective. The reason for such a shortcoming of procedural fairness might be manifold, but it essentially boils down to the mechanical application of the law, excessive formalism in the application and interpretation of the law, and a failure to go beyond mere appearances and assess the realities of the situation complained of. In this paper, I expound on the role of the constitutional complaint as an effective remedy pertinent to individuals who have an arguable claim regarding a violation of their substantive rights guaranteed by the ECHR and the Constitution alike. This paper analyses a ruling of the Constitutional Court of Kosovo where it found a violation of the right to privacy and family life and the right to an effective remedy, notwithstanding the fair conduct of the proceedings. I will also show the impact of the relevant case law of the European Court on the approach and rationale of the Constitutional Court

An Efficient Algorithm for Monitoring Practical TPTL Specifications

We provide a dynamic programming algorithm for the monitoring of a fragment of Timed Propositional Temporal Logic (TPTL) specifications. This fragment of TPTL, which is more expressive than Metric Temporal Logic, is characterized by independent time variables which enable the elicitation of complex real-time requirements. For this fragment, we provide an efficient polynomial time algorithm for off-line monitoring of finite traces. Finally, we provide experimental results on a prototype implementation of our tool in order to demonstrate the feasibility of using our tool in practical applications

Conformance Testing as Falsification for Cyber-Physical Systems

In Model-Based Design of Cyber-Physical Systems (CPS), it is often desirable to develop several models of varying fidelity. Models of different fidelity levels can enable mathematical analysis of the model, control synthesis, faster simulation etc. Furthermore, when (automatically or manually) transitioning from a model to its implementation on an actual computational platform, then again two different versions of the same system are being developed. In all previous cases, it is necessary to define a rigorous notion of conformance between different models and between models and their implementations. This paper argues that conformance should be a measure of distance between systems. Albeit a range of theoretical distance notions exists, a way to compute such distances for industrial size systems and models has not been proposed yet. This paper addresses exactly this problem. A universal notion of conformance as closeness between systems is rigorously defined, and evidence is presented that this implies a number of other application-dependent conformance notions. An algorithm for detecting that two systems are not conformant is then proposed, which uses existing proven tools. A method is also proposed to measure the degree of conformance between two systems. The results are demonstrated on a range of models