Andrei Soeanu

Systems Modeling Language

Systems modeling language (SysML) [187] is a modeling language dedicated to systems engineering applications . It is a UML profile that not only reuses a subset of UML 2.1.1 [186] but also provides additional extensions to better fit SE’s specific needs. These extensions are mainly meant to address the requirements stated in the UML for SE request for proposal (RFP) [177]. It is intended to help specify and architect complex systems and their components and enable their analysis, design, and verification and validation . These systems may consist of heterogeneous components such as hardware , software , information, processes, personnel, and facilities [187].

Automatic Verification and Performance Analysis of Time-Constrained SysML Activity Diagrams

We present in this paper a new approach for the automatic verification and performance analysis of SysML activity diagrams. Since timeliness is important in the design and analysis of real-time systems, we annotate activity diagrams with time constraints. In order to apply the model checking technique, we use discrete-time Markov chains (DTMC) as a semantic interpretation of such SysML models wherein communication is restricted to synchronization. Thus, we describe a mapping procedure of SysML activity diagrams to their corresponding DTMC and use PRISM model checker for the assessment and evaluation of performance characteristics. Finally, we apply our methodology on a real-life case study meant to assess a systems engineering behavioral model of a photo-camera device

A unified approach for verification and validation of systems and software engineering models

We present in this paper a unified paradigm for the verification and validation of software and systems engineering design models expressed in UML 2.0 or SysML. This paradigm relies on an established synergy between three salient approaches, which are model-checking, program analysis, and software engineering techniques. To illustrate the accomplishment of our results, we have designed and implemented an integrated and automated computer-aided assessment tool. We provide three case studies for sequence, state machine, and class and package diagrams to demonstrate the benefits of our methodology

Verification and Validation in Systems Engineering

Verification and validation represents an important process used for the quality assessment of engineered systems and their compliance with the requirements established at the beginning of or during the development cycle. Debbabi and his coauthors investigate methodologies and techniques that can be employed for the automatic verification and validation of systems engineering design models expressed in standardized modeling languages. Their presentation includes a birds eye view of the most prominent modeling languages for software and systems engineering, namely the Unified Modeling Language (UML) and the more recent Systems Modeling Language (SysML). Moreover, it elaborates on a number of quantitative and qualitative techniques that synergistically combine automatic verification techniques, program analysis, and software engineering quantitative methods applicable to design models described in these modeling languages. Each of these techniques is additionally explained using a case study highlighting the process, its results, and resulting changes in the system design. Researchers in academia and industry as well as students specializing in software and systems engineering will find here an overview of state-of-the-art validation and verification techniques. Due to their close association with the UML standard, the presented approaches are also applicable to industrial software development.

The multi-depot split-delivery vehicle routing problem: Model and solution algorithm

Abstract Logistics and supply-chain management may generate notable operational cost savings with increased reliance on shared serving of customer demands by multiple agents. However, traditional logistics planning exhibits an intrinsic limitation in modeling and implementing shared commodity delivery from multiple depots using multiple agents. In this paper, we investigate a centralized model and a heuristic algorithm for solving the multi-depot logistics delivery problem including depot selection and shared commodity delivery. The contribution of the paper is threefold. First, we elaborate a new integer linear programming (ILP) model, namely: Multi-Depot Split-Delivery Vehicle Routing Problem (MDSDVRP) which allows establishing depot locations and routes for serving customer demands within the same objective function. Second, we illustrate a fast heuristic algorithm leveraging knowledge gathering in order to find near-optimal solutions. Finally, we provide performance results of the proposed approach by analyzing known problem instances from different VRP problem classes. The experimental results show that the proposed algorithm exhibits very good performance when solving small and medium size problem instances and reasonable performance for larger instances.

Transportation risk analysis using probabilistic model checking

Elaboration of an approach for transportation risk assessment and contingency evaluation.Modeling risk prone transportation tasks as composed Markov Decision Process (MDP).Assessment of transportation tasks expressed as MDP via probabilistic model checking.Provision of decision making support via decision trees built from the model checking output.Evaluation of risk related properties expressed in probabilistic temporal logic. Transportation and supply chain activities represent essential components in many endeavors covering both public and private domains. However, the underlying transport networks are complex and potentially fragile due to weather, natural disasters or other risk factors. Thus, assessing transportation related risk represents a key decision support capability along with the ability to evaluate contingency options for risk mitigation. In this paper, we address these issues by adopting probabilistic model checking to evaluate the risk and contingency options related to transportation tasks. In this pursuit, risk related properties are assessed for behavioral models capturing the transport system. Moreover, we show the usefulness of constructing decision trees that can provide insightful means of risk appraisal. The proposed approach can help decision makers evaluate contingency options and determine lower and upper cost bounds for risky transportation tasks such as those involved in humanitarian aid provision. The proposed approach is also illustrated with a case study.

Probabilistic Model Checking of SysML Activity Diagrams

Incorporated modeling and analysis of both functional and non-functional aspects of today’s systems behavior represents a challenging issue in the field of formal methods .

A decentralized heuristic for multi-depot split-delivery vehicle routing problem

We introduce a Multi-Point Stochastic Insertion Cost Gradient Descent (MuPSICGD) heuristic algorithm to solve multi-depot split-delivery vehicle routing problem (MDSD-VRP) through an innovative approach. We also describe two solution improvement techniques that can further enhance a fairly good solution. Our contribution is threefold: First we present a heuristic-based mechanism to solve multi-depot, multi-vehicle per depot routing problems in split-delivery setting. Second, unlike related meta-heuristics approaches, we construct solutions from connecting fragments. This can be very helpful in projecting a fitting solution estimate during the searching mechanism along with the potential for adaptability to exogenous events during routing execution. Third, the approach is suitable for decentralized implementation as long as the operating nodes cooperate on solving a common problem instance. In this respect, we elaborate the decentralization procedure. The proposed technique is also resilient to the loss or addition of computing nodes. We also provide a case study, implementation guidelines and suitable benchmarks based on known problem instances.

New aspect-oriented constructs for security hardening concerns

In this paper, we present new pointcuts and primitives to Aspect-Oriented Programming (AOP) languages that are needed for systematic hardening of security concerns. The two proposed pointcuts allow to identify particular join points in a programs control-flow graph (CFG). The first one is the GAFlow, Closest Guaranteed Ancestor, which returns the closest ancestor join point to the pointcuts of interest that is on all their runtime paths. The second one is the GDFlow, Closest Guaranteed Descendant, which returns the closest child join point that can be reached by all paths starting from the pointcut of interest. The two proposed primitives are called ExportParameter and ImportParameter and are used to pass parameters between two pointcuts. They allow to analyze a programs call graph in order to determine how to change function signatures for passing the parameters associated with a given security hardening. We find these pointcuts and primitives to be necessary because they are needed to perform many security hardening practices and, to the best of our knowledge, none of the existing ones can provide their functionalities. Moreover, we show the viability and correctness of the proposed pointcuts and primitives by elaborating and implementing their algorithms and presenting the result of explanatory case studies.

Control Flow Based Pointcuts for Security Hardening Concerns

In this paper, we present two new control flow based point-cuts to Aspect-Oriented Programming (AOP) languages that are needed for systematic hardening of security concerns. They allow to identify particular join points in a program’s control flow graph (CFG). The first proposed primitive is the GAFlow, the closest guaranteed ancestor, which returns the closest ancestor join point to the pointcuts of interest that is on all their runtime paths. The second proposed primitive is the GDFlow, the closest guaranteed descendant, which returns the closest child join point that can be reached by all paths starting from the pointcuts of interest. We find these pointcuts to be necessary because they are needed to perform many security hardening practices and, to the best of our knowledge, none of the existing pointcuts can provide their functionalities. Moreover, we show the viability and correctness of our proposed pointcuts by elaborating and implementing their algorithms and presenting the results of a testing case study.