Purpose Business process (BP) reengineering is defined as reinventing BPs either structurally or technically to achieve dramatic improvements in performance. In any business process reengineering (BPR) project, process modeling is used to reason about problems found in existing (as-is) process and helps to design target (to-be) process. BP model notation is a widely accepted standard for process modeling. “Expressiveness” and “missing formal semantics” are two problems reported to its modeling practices. In existing studies, solutions to these problems are also proposed but still have certain limitations. The paper aims to discuss this issue. Design/methodology/approach In proposed methodology, a meta-model is formally defined that is composed of commonly used modeling elements and their well-formedness rules to check for syntactic and structural correctness of process models. Proposed solution also check semantics of process models and allows to compare as-is and to-be process models for gap identification which is another important aspect of BPR. To achieve the first goal, Z specification is used to provide formal specifications of modeling constructs and their rules and Z3 (an SMT solver) is used for comparisons and verifying properties. Findings Proposed method addresses both “expressiveness” and “missing formal semantics” of BPR models. The results of its evaluation clearly indicate that using formally specified meta-model, BPR model is syntactically and structurally correct. Moreover, formal modeling of BPs in Z3 helped to compare processes and to check control flow properties. Research limitations/implications Although the proposed method is tested on an example that is widely used in BPR literature, the example is only covering modeling elements which are part of the proposed subset and are reported in literature as frequently used modeling elements. A separate detailed study is required to test it on more complex systems. Practical implications Specifying process models using Z specification and Z3 solver requires certain expertise. Originality/value The proposed method adds value to BPR body of knowledge as it proposes a method to ensure structural and syntactic correctness of models, highlighting the importance of verifying run time properties and providing a direction toward comparing process models for gap analysis.

No abstract

No abstract

No abstract

Failure Modes and Effects Analysis (FMEA) is the process of identifying potential failure modes, their causes and effects associated with a product, process or system. In this paper, we discuss the application of FMEA in the design of cybersecurity experiments using a medium interaction server honeypot in an Internet of Things (IoT) environment. Through FMEA analysis, we identify the factors affecting the outcome or contributing to the potential failures of the cybersecurity experiment. We discuss the causes of failures, their effects and how to minimise or mitigate them.