COST Action IC 1402 ArVI: Runtime Verification Beyond Monitoring -- Activity Report of Working Group 1

This report presents the activities of the first working group of the COST Action ArVI, Runtime Verification beyond Monitoring. The report aims to provide an overview of some of the major core aspects involved in Runtime Verification. Runtime Verification is the field of research dedicated to the analysis of system executions. It is often seen as a discipline that studies how a system run satisfies or violates correctness properties. The report exposes a taxonomy of Runtime Verification (RV) presenting the terminology involved with the main concepts of the field. The report also develops the concept of instrumentation, the various ways to instrument systems, and the fundamental role of instrumentation in designing an RV framework. We also discuss how RV interplays with other verification techniques such as model-checking, deductive verification, model learning, testing, and runtime assertion checking. Finally, we propose challenges in monitoring quantitative and statistical data beyond detecting property violation

A completely unique account of enumeration

How can we enumerate the inhabitants of an algebraic datatype? This paper explores a datatype generic solution that works for all regular types and indexed families. The enumerators presented here are provably both complete and unique—they will eventually produce every value exactly once—and fair—they avoid bias when composing enumerators. Finally, these enumerators memoise previously enumerated values whenever possible, thereby avoiding repeatedly recomputing recursive results

Subsea Blowout Preventer (BOP): Design, Reliability, Testing, Deployment, and Operation and Maintenance Challenges

Subsea blowout preventer (BOP) is a safety-related instrumented system that is used in underwater oil drilling to prevent the well to blowout. As oil and gas exploration moves into deeper waters and harsher environments, the setbacks related to reliable functioning of the BOP system and its subsystems remain a major concern for researchers and practitioners. This study aims to systematically review the current state-of-the-art and present a detailed description about some of the recently developed methodologies for through-life management of the BOP system. Challenges associated with the system design, reliability analysis, testing, deployment as well as operability and maintainability are explored, and then the areas requiring further research and development will be identified. A total of 82 documents published since 1980's are critically reviewed and classified according to two proposed frameworks. The first framework categorises the literature based on the depth of water in which the BOP systems operate, with a sub-categorization based on the Macondo disaster. The second framework categorises the literature based on the techniques applied for the reliability analysis of BOP systems, including Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), Reliability Block Diagram (RBD), Petri Net (PN), Markov modelling, Bayesian Network (BN), Monte Carlo Simulation (MCS), etc. Our review analysis reveals that the reliability analysis and testing of BOP has received the most attention in the literature, whereas the design, deployment, and operation and maintenance (O&M) of BOPs received the least

Advancing Deductive Program-Level Verification for Real-World Application: Lessons Learned from an Industrial Case Study

This thesis is concerned with practicability of deductive program verification on source code level. As part of a case study for the verification of real-world software, the specification and verification approach to show correctness of the virtualizing kernel PikeOS is presented. Issues within the verification process using current tools and methodologies are discussed and several aspects of these problems are then addressed in detail to improve the verification process and tool usability

From start-ups to scale-ups: Opportunities and open problems for static and dynamic program analysis

This paper describes some of the challenges and opportunities when deploying static and dynamic analysis at scale, drawing on the authors' experience with the Infer and Sapienz Technologies at Facebook, each of which started life as a research-led start-up that was subsequently deployed at scale, impacting billions of people worldwide. The paper identifies open problems that have yet to receive significant attention from the scientific community, yet which have potential for profound real world impact, formulating these as research questions that, we believe, are ripe for exploration and that would make excellent topics for research projects