Connectivity of workflow nets : the foundations of stepwise verification

Behavioral models capture operational principles of real-world or designed systems. Formally, each behavioral model defines the state space of a system, i.e., its states and the principles of state transitions. Such a model is the basis for analysis of the system’s properties. In practice, state spaces of systems are immense, which results in huge computational complexity for their analysis. Behavioral models are typically described as executable graphs, whose execution semantics encodes a state space. The structure theory of behavioral models studies the relations between the structure of a model and the properties of its state space. In this article, we use the connectivity property of graphs to achieve an efficient and extensive discovery of the compositional structure of behavioral models; behavioral models get stepwise decomposed into components with clear structural characteristics and inter-component relations. At each decomposition step, the discovered compositional structure of a model is used for reasoning on properties of the whole state space of the system. The approach is exemplified by means of a concrete behavioral model and verification criterion. That is, we analyze workflow nets, a well-established tool for modeling behavior of distributed systems, with respect to the soundness property, a basic correctness property of workflow nets. Stepwise verification allows the detection of violations of the soundness property by inspecting small portions of a model, thereby considerably reducing the amount of work to be done to perform soundness checks. Besides formal results, we also report on findings from applying our approach to an industry model collection

The triconnected abstraction of process models

Companies use business process models to represent their working procedures in order to deploy services to markets, to analyze them, and to improve upon them. Competitive markets necessitate complex procedures, which lead to large process specifications with sophisticated structures. Real world process models can often incorporate hundreds of modeling constructs. While a large degree of detail complicates the comprehension of the processes, it is essential to many analysis tasks. This paper presents a technique to abstract, i.e., to simplify process models. Given a detailed model, we introduce abstraction rules which generalize process fragments in order to bring the model to a higher abstraction level. The approach is suited for the abstraction of large process specifications in order to aid model comprehension as well as decomposing problems of process model analysis. The work is based on process structure trees that have recently been introduced to the field of business process management

Analisa Similaritas Model Proses Bisnis Menggunakan Metode Hybrid Probabilistic Latent Semantic Analysis (Plsa) Dan Weighted Directed Acyclic Graph (Wdag)

Kebutuhan perusahaan atau organisasi dalam melakukan analisis model proses bisnis diharapkan agar perusahaan maupun organisasi dapat memahami proses yang berjalan serta dapat digunakan sebagai alat untuk membantu perusahaan dalam menghadapi perubahan dan perkembangan sehingga dapat mempermudah pengambilan kebijakan yang dibutuhkan dalam menghadapi perubahan dengan cepat, misalnya pemanfaatan proses yang telah berjalan untuk digunakan dalam proses lain (reusable). Tahap awal dalam penerapan reusable proses adalah mengetahui sub proses yang menyusun proses keseluruhan, tahap berikutnya melakukan analisis terhadap sub-proses dan menghitung nilai similaritas diantara sub-proses yang dibandingkan. Pada penelitian ini akan dibahas metode dekomposisi untuk mengetahui sub-proses yang menyusun proses keseluruhan dari model proses bisnis menggunakan Refined Process Structure Tree (RPST) dan Single Entry and Single Exit (SESE), setelah itu dilakukan analisis menggunakan analisis gabungan dalam menentukan nilai similaritas diantara sub-proses. Metode analisis gabungan yang kami ajukan menggunakan Weighted Directed Acyclic Graph (WDAG) untuk analisa struktural dan Probabilistic Latent Semantic Analysis (PLSA) untuk analisa teekstual dengan tujuan mendapatkan hasil yang lebih baik dari pada menggunakan analisa struktural saja. Studi kasus dalam penelitian ini menggunakan proses bisnis Penerimaan Peserta Didik Baru (PPDB), dengan menggunakan metode diatas proses bisnis PPDB lebih mudah dianalisa sehingga membantu perusahaan atau organisasi dalam menghadapi perubahan secara cepat dan tepat =========================================================================================== Needs of the company or organization in analyzing business process models is expected that companies and organizations can understand the processes that are running and can be used as a tool to help companies in the face of change and development so as to facilitate the decision making required in the face of change quickly, for example, the use of process have gone on to be used in another process (reusable). The initial stage in the application process is knowing reusable sub-processes that make up the whole process, the next stage of the analysis of sub-processes and calculate the value of similarity between the subprocesses that are compared. In this research will be discussed decomposition method to determine the sub-processes that make up the overall process of business process models using the Refined Process Structure Tree (RPST) and Single Entry and Single Exit (SESE), then analyzed using analysis combined in determining the value of similarity between sub process. The combined analysis method that we propose to use Weighted Directed Acyclic Graph (WDAG) for structural analysis and Probabilistic Latent Semantic Analysis (PLSA) for textual analysis in order to get better results from the structural analysis only. The case studies in this study using a business process Admission New Students (PPDB), using the above method PPDB business processes more easily analyzed and can help change quickly and accurately with the developmen