Transforming an enterprise model into a use case model in business process systems
TL;DR: This study presents the source and target metamodels, a set of transformation rules, and a tool to support the transformation, and results indicate that the approach can be used in practice, as it did not influence the quality of the generated use cases.
About: This article is published in Journal of Systems and Software.The article was published on 2014-10-01. It has received 10 citations till now. The article focuses on the topics: Requirement & Enterprise systems engineering.
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TL;DR: The role of business process orientation (BPO) at intra-and inter-organizational levels in various aspects of organizational performance is investigated in this paper, where a comprehensive research model is developed based on the review of literature.
Abstract: Purpose – The purpose of this paper is to investigate the role of business process orientation (BPO) at intra- and inter-organizational levels in various aspects of organizational performance. Design/methodology/approach – A comprehensive research model is developed based on the review of literature. The research model is later examined and modified based on the analysis of a sample of 3,200 for-profit organizations. Factor analysis and structural equation modeling techniques are used to investigate the research questions presented in the study. Findings – The findings of this study suggest that while higher levels of BPO at intra-organizational level provide direct financial and operational benefits for the firms in our sample. Higher levels of BPO at inter-organizational level provide direct customer satisfaction benefits as well as indirect financial and operational benefits. Research limitations/implications – Lack of sufficient previous studies and theories in this area is one of the main limitations...
21 citations
22 Nov 2016
TL;DR: A systematic mapping study that aims at understanding the trends and characteristics of concrete model transformations published in the past decade and shows that the number of papers with, as main contribution, a concrete transformation solution, is not as high as expected.
Abstract: As a contribution to the adoption of the Model-Driven Engineering (MDE) paradigm, the research community has proposed concrete model transformation solutions for the MDE infrastructure and for domain-specific problems. However, as the adoption increases and with the advent of the new initiatives for the creation of repositories, it is legitimate to question whether proposals for concrete transformation problems can be still considered as research contributions or if they respond to a practical/technical work. In this paper, we report on a systematic mapping study that aims at understanding the trends and characteristics of concrete model transformations published in the past decade. Our study shows that the number of papers with, as main contribution, a concrete transformation solution, is not as high as expected. This number increased to reach a peak in 2010 and is decreasing since then. Our results also include a characterization and an analysis of the published proposals following a rigorous classification scheme.
14 citations
Cites background from "Transforming an enterprise model in..."
...Half of those are implemented in languages considered de facto standards (ATL [26] and QVT [39]), and the other half with less popular languages [25, 41]....
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...Orientation Does the transformation involve an author from industry or only academic authors are concerned? or QVT [17]....
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...Most of the papers involving source and/or target domain-specific metamodels deal with business concerns, like QoS in [31] and business models in [39]....
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...Nevertheless, most validations were performed on small examples [39] which reduces the scalability of the validation to its peculiar context....
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01 Dec 2014
TL;DR: A solution to reduce risks using UML visualization of software processes in detail, and V-Model (Software Development Lifecycle Model) techniques are performed to produce verified results in each phase of development lifecycle.
Abstract: Risk Assessment is one of the most critical parts of software engineering process, and risks are the factors that could be results in software failure if they are not correctly handled. In this Paper, we propose a solution to reduce risks using UML visualization of software processes in detail, and V-Model (Software Development Lifecycle Model) techniques are performed to produce verified results in each phase of development lifecycle. Using all above aspects and research findings, we propose “Risk Assessment V-Model”. Furthermore, we use “Do Sale Process” to discuss different properties of our model. This model is quite in general and can be applicable and expendable for many kinds of software systems.
6 citations
01 Jan 2017
TL;DR: A top-down decomposition approach is proposed to specify requirements and analyse change impact on BPMN models at different stages of the business process lifecycle.
Abstract: When performing functional requirements analysis, software developers need to understand the application domain to fulfil organizational needs. This is essential for making trade-off decisions and achieving the success of the software development project. An application domain is dealt within the modelling phase of the business process lifecycle. Assuming that functional changes are inevitable, we propose to use the standard COSMIC to evaluate these changes and provide indicators of change status in the business domain. Expressing functional changes in terms of COSMIC Function Point units can be helpful in identifying changes leading to potential impact on the business process's functional size. In addition, we propose a top-down decomposition approach to specify requirements and analyse change impact on BPMN models at different
6 citations
03 Jul 2019
TL;DR: A Model Driven Architecture (MDA) compliant methodology that aims to automate the generation of UML models from BPMN models that respects the best-practice granularity level of a use case is proposed.
Abstract: The necessity of aligning an enterprise’s Information System (IS) model to its Business Process (BP) model is incontestable. However, the main difficulty of establishing/maintaining BP-IS models alignment stems from the dissimilarities in the knowledge of the information system developers and the business process experts. To face these predicaments, we propose a Model Driven Architecture (MDA) compliant methodology that aims to automate the generation of UML models from BPMN models. It allows mastering transformation from Computation Independent Model (CIM) to Platform Independent Model (PIM). The CIM level expresses the BP, which is modelled through the standard BPMN (Business Process Modelling Notation) and, at the PIM level represents the aligned, IS model is generated as use case diagram. Its originality resides in the CIM to PIM transformation which accounts for the BP structural and semantic perspectives in order to generate an aligned IS model that respects the best-practice granularity level of a use case.
5 citations
References
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Book•
01 Jan 1982
TL;DR: In this article, the authors present a comprehensive overview of the statistical properties of point estimates and their relationship with the probability of a given point in a single-sample set of data.
Abstract: 1. OVERVIEW AND DESCRIPTIVE STATISTICS. Populations, Samples, and Processes. Pictorial and Tabular Methods in Descriptive Statistics. Measures of Location. Measures of Variability. 2. PROBABILITY. Sample Spaces and Events. Axioms, Interpretations, and Properties of Probability. Counting Techniques. Conditional Probability. Independence. 3. DISCRETE RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Random Variables. Probability Distributions for Discrete Random Variables. Expected Values. The Binomial Probability Distribution. Hypergeometric and Negative Binomial Distributions. The Poisson Probability Distribution. 4. CONTINUOUS RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS. Probability Density Functions. Cumulative Distribution Functions and Expected Values. The Normal Distribution. The Exponential and Gamma Distributions. Other Continuous Distributions. Probability Plots. 5. JOINT PROBABILITY DISTRIBUTIONS AND RANDOM SAMPLES. Jointly Distributed Random Variables. Expected Values, Covariance, and Correlation. Statistics and Their Distributions. The Distribution of the Sample Mean. The Distribution of a Linear Combination. 6. POINT ESTIMATION. Some General Concepts of Point Estimation. Methods of Point Estimation. 7. STATISTICAL INTERVALS BASED ON A SINGLE SAMPLE. Basic Properties of Confidence Intervals. Large-Sample Confidence Intervals for a Population Mean and Proportion. Intervals Based on a Normal Population Distribution. Confidence Intervals for the Variance and Standard Deviation of a Normal Population. 8. TESTS OF HYPOTHESIS BASED ON A SINGLE SAMPLE. Hypotheses and Test Procedures. z Tests for Hypotheses About a Population Mean. The One-Sample t Test. Tests Concerning a Population Proportion. Further Aspects of Hypothesis Testing. 9. INFERENCES BASED ON TWO SAMPLES. z Tests and Confidence Intervals for a Difference between Two Population Means. The Two-Sample t Test and Confidence Interval. Analysis of Paired Data. Inferences Concerning a Difference between Population Proportions. Inferences Concerning Two Population Variances. 10. THE ANALYSIS OF VARIANCE. Single-Factor ANOVA. Multiple Comparisons in ANOVA. More on Single-Factor ANOVA. 11. MULTIFACTOR ANALYSIS OF VARIANCE. Two-Factor ANOVA with Kij = 1. Two-Factor ANOVA with Kij > 1. Three-Factor ANOVA 11. 4 2p Factorial Experiments. 12. SIMPLE LINEAR REGRESSION AND CORRELATION. The Simple Linear Regression Model. Estimating Model Parameters. Inferences About the Slope Parameter ss1. Inferences Concerning Y*x* and the Prediction of Future Y Values. Correlation. 13. NONLINEAR AND MULTIPLE REGRESSION. Assessing Model Adequacy. Regression with Transformed Variables. Polynomial Regression. Multiple Regression Analysis. Other Issues in Multiple Regression. 14. GOODNESS-OF-FIT TESTS AND CATEGORICAL DATA ANALYSIS. Goodness-of-Fit Tests When Category Probabilities Are Completely Specified. Goodness-of-Fit Tests for Composite Hypotheses. Two-Way Contingency Tables 15. DISTRIBUTION-FREE PROCEDURES. The Wilcoxon Signed-Rank Test. The Wilcoxon Rank-Sum Test. Distribution-Free Confidence Intervals. Distribution-Free ANOVA. 16. QUALITY CONTROL METHODS. General Comments on Control Charts. Control Charts for Process Location. Control Charts for Process Variation. Control Charts for Attributes. CUSUM Procedures. Acceptance Sampling.
2,313 citations
Book•
16 Jun 2012
TL;DR: The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments, and provides indispensable information regarding empirical Studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys.
Abstract: Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools. The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a cookbook when evaluating new methods or techniques before implementing them in their organization.
2,079 citations
Book•
01 Jan 2000
TL;DR: Object technology expert Alistair Cockburn borrows from his extensive experience in this realm, and expands on the classic treatments of use cases to provide software developers with a "nuts-and-bolts" tutorial for writing use cases.
Abstract: From the Publisher:
Writing use cases as a means of capturing the behavioral requirements of software systems and business processes is a practice that is quickly gaining popularity. Use cases provide a beneficial means of project planning because they clearly show how people will ultimately use the system being designed. On the surface, use cases appear to be a straightforward and simple concept. Faced with the task of writing a set of use cases, however, practitioners must ask: "How exactly am I supposed to write use cases?" Because use cases are essentially prose essays, this question is not easily answered, and as a result, the task can become formidable.
In Writing Effective Use Cases, object technology expert Alistair Cockburn presents an up-to-date, practical guide to use case writing. The author borrows from his extensive experience in this realm, and expands on the classic treatments of use cases to provide software developers with a "nuts-and-bolts" tutorial for writing use cases. The book thoroughly covers introductory, intermediate, and advanced concepts, and is, therefore, appropriate for all knowledge levels. Illustrative writing examples of both good and bad use cases reinforce the author's instructions. In addition, the book contains helpful learning exerciseswith answersto illuminate the most important points.
Highlights of the book include:
A thorough discussion of the key elements of use casesactors, stakeholders, design scope, scenarios, and more A use case style guide with action steps and suggested formats An extensive list of time-saving use case writing tips Ahelpful presentation of use case templates, with commentary on when and where they should be employed A proven methodology for taking advantage of use cases
With this book as your guide, you will learn the essential elements of use case writing, improve your use case writing skills, and be well on your way to employing use cases effectively for your next development project.
1,644 citations
01 Jan 1995
TL;DR: This thesis proposes a modelling framework i* (pronounced i-star) consisting of two modelling components: the Strategic Dependency (SD) model and the Strategic Rationale (SR) model, which describes a process in terms of intentional dependency relationships among agents.
Abstract: Existing models for describing a process (such as a business process or a software development process) tend to focus on the "what" or the "how" of the process. For example, a health insurance claim process would typically be described in terms of a number of steps for assessing and approving a claim. In trying to improve or redesign a process, however, one also needs to have an understanding of the "why"--for example, why do physicians submit treatment plans to insurance companies before giving treatment? and why do claims managers seek medical opinions when assessing treatment plans? An understanding of the motivations and interests of process participants is often crucial to the successful redesign of processes.
This thesis proposes a modelling framework i* (pronounced i-star) consisting of two modelling components. The Strategic Dependency (SD) model describes a process in terms of intentional dependency relationships among agents. Agents depended on each other for goals to be achieved, tasks to be performed, and resources to be furnished. Agents are intentional in that they have desires and wants, and strategic in that they are concerned about opportunities and vulnerabilities. The Strategic Rationale (SR) model describes the issues and concerns that agents have about existing processes and proposed alternatives, and how they might be addressed, in terms of a network of means-ends relationships. An agent's routines for carrying out a process can be analyzed for their ability, workability, viability and believability. Means-ends rules are used to suggest methods for addressing issues, related issues to be raised, and assumptions to be challenged. The models are represented in the conceptual modelling language Telos. The modelling concepts are axiomatically characterized.
The utility of the framework is illustrated each of four application areas: requirements engineering, business process reengineering, organizational impacts analysis, and software process modelling. Advantage of i* over existing modelling techniques in each of these areas are described.
1,560 citations
TL;DR: This paper presents a meta-modelling framework for estimating the probabilities of different types of population sizes using a simple linear Regression model, and some examples show how this model can be modified to accommodate diverse population sizes.
1,406 citations