Conformance Checking Research Articles

A new simplex-based approach predicting olive oil blend compositions from fatty acid data

Olive oils represent complex matrices varying from pure to heterogeneous varietal contents. Quantitative analysis of co-occurring components is fundamental for conformity checking and adulteration alerting (fighting) of commercial oils. Proportions of co-occurring components are governed by additive-dilutive processes which obey to simplex rule. Using simplex rule, we developed an original computational approach to predict proportions of different co-occurring oil varieties from quantitative chemical features of blends. The approach consisted in applying a complete set of N mixtures between different olive oil varieties by gradually varying their proportions. The N simulated mixtures were characterized by N average fatty acid (FA) profiles calculated from N combinations of randomly sampled individual profiles. After k iterations of the mixture design, the k sets of N FA average profiles were used as input in a discriminant analysis to predict proportions of co-occurring olive oil varieties in different blends. Illustrative application concerned blends made by three main French mono-varietal virgin olive oils (Aglandau, Grossane and Salonenque) and benefiting from Protected Designation of Origin label. Predictive model was validated on outside blends and showed prediction errors with an order of 10% susceptible of reduction by applying a larger mixture design.

Sequence Matching Analysis for Curriculum Development

Many organizations apply information technologies to support their business processes. Using the information technologies, the actual events are recorded and utilized to conform with predefined model. Conformance checking is an approach to measure the fitness and appropriateness between process model and actual events. However, when there are multiple events with the same timestamp, the traditional approach unfit to result such measures. This study attempts to develop a sequence matching analysis. Considering conformance checking as the basis of this approach, this proposed approach utilizes the current control flow technique in process mining domain. A case study in the field of educational process has been conducted. This study also proposes a curriculum analysis framework to test the proposed approach. By considering the learning sequence of students, it results some measurements for curriculum development. Finally, the result of the proposed approach has been verified by relevant instructors for further development.

Constraint-based reasoning on declarative process execution with the logics workbench

Purpose – An integral part of declarative process modelling is to guarantee that the execution of a declarative workflow is compliant with the respective business rules. The purpose of this paper is to establish a formal framework for representing business rules and determining whether any business rules are violated during the executions of declarative process models. Design/methodology/approach – In the approach, a business rule is phrased in terms of restricted English that is related to a constraint template. Linear temporal logic (LTL) is employed as a formalism for defining the set of constraint templates. By exploiting the theorem-proving feature of the Logics Workbench (LWB), business rule violations are then detected in an automatic manner. Findings – This study explored the viability of encoding: first, process executions by means of LTL and second, business rules in terms of restricted English that built upon pattern-oriented templates and LTL. The LWB was used for carrying out temporal reasoning through automated techniques. The applicability of the formal verification approach was exemplified by a case study concerning supply chain management. The findings showed that practical reasoning could be achieved by combining declarative process modelling, restricted English, pattern-oriented templates, LTL and LWB. Originality/value – First, new business rule templates are proposed; second, business rules are expressed in restricted English instead of graphical constructs; third, both finite execution trace and business rules are grounded in LTL. There is no need to deal with the semantic differences between different formalisms; and finally, the theorem prover LWB is used for the conformance checking of a finite execution trace against business rules.

Conformance checking of PMI representation in CAD model STEP data exchange files

Recommended practices supplement data exchange standards by providing common implementation guidance associated with specific requirements. ISO 10303 (STEP) product data exchange files that conform to recommended practices ensure interoperability between computer-aided design (CAD) systems and with downstream applications such as manufacturing and inspection. Correct implementation of product and manufacturing information (PMI)–annotations associated with a CAD model’s edges and faces such as geometric tolerances, dimensional tolerances, and datum features–in CAD authoring systems and translators is essential for interoperability. This paper discusses an approach implemented in a software tool for checking the conformance of STEP files to the recommended practice for PMI representation.

Aggregation by Provenance Types: A Technique for Summarising Provenance Graphs

As users become confronted with a deluge of provenance data, dedicated techniques are required to make sense of this kind of information. We present Aggregation by Provenance Types, a provenance graph analysis that is capable of generating provenance graph summaries. It proceeds by converting provenance paths up to some length k to attributes, referred to as provenance types, and by grouping nodes that have the same provenance types. The summary also includes numeric values representing the frequency of nodes and edges in the original graph. A quantitative evaluation and a complexity analysis show that this technique is tractable; with small values of k, it can produce useful summaries and can help detect outliers. We illustrate how the generated summaries can further be used for conformance checking and visualization.

Editorial

This introduction to the special issue on Business Process Intelligence (BPI) discusses the relation between data and processes. The recent attention for Big Data illustrates that organizations are aware of the potential of the torrents of data generated by today's information systems. However, at the same time, organizations are struggling to extract value from this overload of data. Clearly, there is a need for data scientists able to transform event data into actionable information. To do this, it is crucial to take a process perspective. The ultimate goal of BPI is not to improve information systems or the recording of data; instead the focus should be in improving the process. For example, we may want to aim at reducing costs, minimizing response times, and ensuring compliance. This requires a “confrontation” between process models and event data. Recent advances in process mining allow us to automatically learn process models showing the bottlenecks from “raw” event data. Moreover, given a normative model, we can use conformance checking to quantify and understand deviations. Automatically learned models may also be used for prediction and recommendation. BPI is rapidly developing as a field linking data science to business process management. This article aims to provide an overview thereby paving the way for the other contributions in this special issue.

Conformance Checking and QoS Selection Based on CPN for Web Service Composition

The development of new services by composition of existing ones has gained considerable momentum as a means of integrating heterogeneous applications and realizing business collaborations. More and more Web services with similar function attributes but different QoS are available. The performance of the composed service is determined by the involved Web services. Therefore, QoS properties are crucial for selecting the Web services to take part in the composition, which can identify the best candidate Web services from a set of functionally-equivalent services. Web service composition enables seamless and dynamic integration of business applications on the web. Due to the inherent autonomy and heterogeneity of component Web services, it is difficult to predict the behavior of the overall composite service. Conformance checking identifies failure and conflict of execution of composite Web service that ensures reliable execution. In this paper we use skyline computation to select services for composition efficiently, reducing the number of candidate services to be considered. Then a novel color Petri net model of Web service composition is presented that combines QoS-based optimal service selection and consistence verification. In the model we define aggregation functions, and use a Multiple Attribute Decision Making approach for the utility function to achieve optimal services selection of QoS properties. We also propose a consistence verification approach to identify potential logical inconsistence of the semantic Web service process before the deployment. Proofs are also presented. We evaluate our approach experimentally using both real and synthetically generated datasets.

Balanced multi-perspective checking of process conformance

Organizations maintain process models that describe or prescribe how cases (e.g., orders) are handled. However, reality may not agree with what is modeled. Conformance checking techniques reveal and diagnose differences between the behavior that is modeled and what is observed. Existing conformance checking approaches tend to focus on the control-flow in a process, while abstracting from data dependencies, resource assignments, and time constraints. Even in those situations when other perspectives are considered, the control-flow is aligned first, i.e., priority is given to this perspective. Data dependencies, resource assignments, and time constraints are only considered as second-class citizens, which may lead to misleading conformance diagnostics. For example, a data attribute may provide strong evidence that the wrong activity was executed. Existing techniques will still diagnose the data-flow as deviating, whereas our approach will indeed point out that the control-flow is deviating. In this paper, a novel algorithm is proposed that balances the deviations with respect to all these perspectives based on a customizable cost function. Evaluations using both synthetic and real data sets show that a multi-perspective approach is indeed feasible and may help to circumvent misleading results as generated by classical single-perspective or staged approaches.

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This paper is dedicated to a tool whose aim is to facilitate process mining experiments and evaluation of the repair algorithms. Process mining is a set of approaches which provides solutions and algorithms for discovery and analysis of business process models based on event logs. Process mining has three main areas of interest: model discovery, conformance checking and enhancement. The paper focuses on the latter. The goal of enhancement process is to refine an existing process model in order to make it adhere event logs. The particular approach of enhancement considered in the paper is called decomposed model repair. Although the paper is devoted to the implementation part of the approach, theoretical preliminaries essential for domain understanding are provided. Moreover, a typical use case of the tool is shown as well as guides to extending the tool and enriching it with extra algorithms and functionality. Finally, other solutions which can be used for implementation of repair schemes are considered, pros and cons of using them are mentioned.

Model checking as support for inspecting compliance to rules in flexible processes

Context: In backing business processes with information technology, a difficult trade-off appears between the desire to control processes for avoiding undesirable executions, and the flexibility that users need in order to attain their higher level goals. While this is a general trend in general business processes, it is even more acute in specific domains like the medical area, where the clinical guidelines are expected to contribute to the optimization of medical assistance.Objective: We study model checking as support for understanding and solving the inconsistencies between the process models and their corresponding execution. The aim is to provide various human users with output in controlled English for the checking of properties about the execution of such processes, and perhaps input in controlled English for properties of interest from the point of view of the user.Method: For the conformance checking of such complex situations, we use an extended version of a Hybrid Logics model checking tool, for the verification of various properties within an abstract representation model. The extension with Description Logics helps to exploit a more refined representation of the entities involved in the execution of processes. The advantages of using the model checker in visualizing and verbalizing connections of the properties checked with their dependencies over time are shown on a sore throat running scenario, relative to its corresponding clinical guidelines.Results: With new data for an alternative run of the execution, our method can update the abstract model to enable the user to see what might happen or might have happened in such runs of the process model. The new updated abstract model corresponding to the new real situations is then used to analyze whether the overall state is acceptable or should further actions be considered to arrive at an acceptable state of the world.Conclusion: Our results show how the combination of Hybrid Logic and Description Logic can provide the necessary abstraction for the checking to be carried out at a level understandable by the human user when the properties of interest can be translated by a controlled English language interface.

A toolset for conformance testing against UML sequence diagrams based on event-driven colored Petri nets

Novel techniques and a toolset are presented for automatically testing the conformance of software implementations against partial behavioral models constituted by a set of parameterized UML sequence diagrams, describing both external interactions with users or client applications and internal interactions between objects in the system. Test code is automatically generated from the sequence diagrams and executed on the implementation under test, and test results and coverage information are presented back visually in the model. A runtime test library handles internal interaction checking, test stubs, and user interaction testing, taking advantage of aspect-oriented programming techniques. Incremental conformance checking is achieved by first translating sequence diagrams to Extended Petri Nets that combine the characteristics of Colored Petri Nets and Event-Driven Petri Nets.

PACS Displays: How to Select the Right Display Technology

The medical imaging display is a precision instrument with many features not found in commercial-grade displays. The more one understands what these features are and their corresponding clinical value, the better one can make a purchase decision. None of these displays maintain themselves for 5 years or more without some degree of automatic or manual performance testing. Routine calibration conformance checks are beginning to be mandated by the departments of health of many states. Most manufacturers provide mechanisms to perform these checks and keep track of their results, some more easily than others. Aconsistent display brightness of about 400 cd/m(2) and close conformance to the DICOM curve are the key components of a successful check. Displays are typically characterized by the number of pixels they contain, usually 2, 3, or 5 megapixels, but this is the least useful determinant of image quality. What matters most is the size of the pixels and the size of the whole display, which should be selected on the basis of the typical viewing distance. The farther one's eyes are from the display, the larger the pixels and the overall display size can be while still feeding the eye as much information as it can see. Care should be taken to use the appropriate display in a given setting for the clinical purpose at hand.

River basin management plans developed in Greece, based on the WFD 2000/60/EC guidelines

The Water Framework Directive 2000/60/EC (WFD) sets an overall framework for water management in Europe. The main instrument for its implementation is the river basin management plan (RBMP) and the accompanying programme of measures. As we are almost in the end of the WFD implementation cycle (in 2015), the paper presents the progress regarding the RBMPs developed by each EU27 member state (MS). A review of the conformity checks regarding the obligation and the quality of the RBMPs is provided for all EU27 MS. Special focus is given to Greece attempting a comparative analysis of its RBMPs. Although they comply with the context requirements set by the WFD, there have been problems occurring as consequences intense disputes. Special focus is given in the economic assessment. Different methodologies used and the lack of data are the main problems identified.

Preserving architectural decisions through architectural patterns

Architectural decisions have emerged as a means to maintain the quality of the architecture during its evolution. One of the most important decisions made by architects are those about the design approach such as the use of patterns or styles in the architecture. The structural nature of this type of decisions give them the potential to be controlled systematically. In the literature, there are some works on the automation of architectural decision violation checking. In this paper we show that these works do not allow to detect all possible architectural decision violations. To solve this problem we propose an approach which: (i) describes architectural patterns that hold the architectural decision definition, (ii) integrates architectural decisions into an architectural model and, (iii) automates the architectural decision conformance checking. The approach is implemented using Eclipse modeling framework and its accompanying technologies. Starting from well-known architectural patterns, we show that we can formalize all those related to the structural aspect. Through two evaluations, we show that our approach can be adapted to different architecture paradigms and allows to detect more violations comparing to the existing approaches.

Source code and design conformance, design pattern detection from source code by classification approach

Nowadays, software designers attempt to employ design patterns in software design phase, but design patterns may be not used in the implementation phase. Therefore, one of the challenging issues is conformance checking of source code and design, i.e., design patterns. In addition, after developing a system, usually its documents are not maintained, so, identifying design pattern from source code can help to achieve the design of an existing system as a reverse engineering task. The variant implementations (i.e., different source codes) of a design pattern make hard to detect the design pattern instances from the source code. To address this issue, in this paper, we propose a new method which aims to map the design pattern detection problem into a learning problem. The proposed design pattern detector is made by learning from the information extracted from design pattern instances which normally include variant implementations. To evaluate the proposed method, we applied it on open source codes to detect six different design patterns. The experimental results show that the proposed method is promising and effective.

The RD53 collaboration's SystemVerilog-UVM simulation framework and its general applicability to design of advanced pixel readout chips

The foreseen Phase 2 pixel upgrades at the LHC have very challenging requirements for the design of hybrid pixel readout chips. A versatile pixel simulation platform is as an essential development tool for the design, verification and optimization of both the system architecture and the pixel chip building blocks (Intellectual Properties, IPs). This work is focused on the implemented simulation and verification environment named VEPIX53, built using the SystemVerilog language and the Universal Verification Methodology (UVM) class library in the framework of the RD53 Collaboration. The environment supports pixel chips at different levels of description: its reusable components feature the generation of different classes of parameterized input hits to the pixel matrix, monitoring of pixel chip inputs and outputs, conformity checks between predicted and actual outputs and collection of statistics on system performance. The environment has been tested performing a study of shared architectures of the trigger latency buffering section of pixel chips. A fully shared architecture and a distributed one have been described at behavioral level and simulated; the resulting memory occupancy statistics and hit loss rates have subsequently been compared.

The target-setting process in the CO2 Performance Ladder: does it lead to ambitious goals for carbon dioxide emission reduction?

Energy management and carbon accounting schemes are increasingly being adopted as a corporate response to climate change. These schemes often demand the setting of ambitious targets for the reduction of corporate greenhouse gas emissions. However, only limited empirical insight is available regarding the companies' target-setting process and the auditing practice of certification agencies that evaluate ambition levels of greenhouse gas reduction targets. We studied the target-setting process of firms participating in the CO2 Performance Ladder. The CO2 Performance Ladder is a new certifiable scheme for energy management and carbon accounting that is used as a tool for green public procurement in the Netherlands. This study aimed at answering the question ‘To what extent does the current target-setting process in the CO2 Performance Ladder lead to ambitious CO2 emission reduction goals?’. An exploratory research design was used as the main research approach for this study. Data were collected through interviews with relevant stakeholders (companies, consultants, auditors and scheme owner), document reviews of the certification scheme, and monitoring reports. The research findings indicated that several certification requirements for setting CO2 emission reduction targets were interpreted differently by the various actors. Conformity checks by the auditors did not always include a full assessment of all certification requirements because of the lack of well-defined assessment criteria. The research results also indicated that corporate CO2 emission reduction targets were not ambitious. The analysis of the target-setting process revealed that there was a semi-structured bottom-up auditing practice for evaluating the corporate CO2 emission reduction targets, but the final assessments of whether target levels were sufficiently ambitious were not very well defined. The main conclusion is that the current target-setting process in the CO2 Performance Ladder did not necessarily lead to the establishment of the most ambitious goals for CO2 emission reduction. Other approaches for setting target levels, such as minimum performance levels, must be considered to maintain the CO2 Performance Ladder as a valid tool for green public procurement.

Adaptive Process Simplification and Conformance Checking in Event Logs

In this paper, we used two classes of process mining techniques (i.e., Discovery and Conformance Analysis) in order to discover models and organizational structures related to the handling of proceedings’ peer reviews in an international conference in Thailand. We monitored the deviations, comparing the observed events (real-life data) with the predefined models, as well. Knowing that ProM plugins receive the input logs only in MXML (Mining eXtensible Markup Language) and XES (eXtensible Event Stream) formats, we chose ProMimport as a framework to extract MXML log from an event log consisted of 87 cases (papers) and 3267 events. Alpha (α) Algorithm, Heuristic, Fuzzy and Social Network mining techniques (from Discovery class) were applied to automatically construct the proceedings’ review models, primarily without any priori model. Though the Heuristic Miner closely followed the Alpha algorithm, the technique had the privilege to derive XOR and AND connectors from dependency relations of the event log. Next, the actual process behavior was projected onto fuzzy models. The result was an animation movie coming up with a better understanding of what has occurred in reality. Also, using Social Network Miner technique we could analyze the organizational perspective of the peer review process in terms of three metrics, namely as: (a) Handover of Work, (b) Working Together, and (c) Similar Tasks. Alternatively, having a priori model for review of the proceedings, we used LTL Checker and Performance Analysis techniques (from Conformance Checker class) to identify discrepancies between the log and the pre-defined model. After applying the LTL checking approach, the deviations were detected — leading to enrich the real model. In addition, Performance Analysis technique made us capable of projecting the bottlenecks all through the peer review system. In general, one of the main benefits of the techniques used in this paper is that information is objectively compiled. To say simple, we gathered valuable information about what actually was happening according to the review process of the papers and existing bottlenecks, and not what we just thought or expected to see happening in the event log. Considering the results of the study, conference committee chairs can better evaluate the performance of the involving reviewers (as well as team members) within the assigned tasks. This will improve the performance, efficiency and effectiveness of the handling of reviews for prospective academic/educational conferences.

Online treatment compliance checking for clinical pathways.

Compliance checking for clinical pathways (CPs) is getting increasing attention in health-care organizations due to stricter requirements for cost control and treatment excellence. Many compliance measures have been proposed for treatment behavior inspection in CPs. However, most of them look at aggregated data seen from an external perspective, e.g. length of stay, cost, infection rate, etc., which may provide only a posterior impression of the overall conformance with the established CPs such that in-depth and in near real time checking on the compliance of the essential/critical treatment behaviors of CPs is limited. To provide clinicians real time insights into violations of the established CP specification and support online compliance checking, this article presents a semantic rule-based CP compliance checking system. In detail, we construct a CP ontology (CPO) model to provide a formal grounding of CP compliance checking. Using the proposed CPO, domain treatment constraints are modeled into Semantic Web Rule Language (SWRL) rules to specify the underlying treatment behaviors and their quantified temporal structure in a CP. The established SWRL rules are integrated with the CP workflow such that a series of applicable compliance checking and evaluation can be reminded and recommended during the pathway execution. The proposed approach can, therefore, provides a comprehensive compliance checking service as a paralleling activity to the patient treatment journey of a CP rather than an afterthought. The proposed approach is illustrated with a case study on the unstable angina clinical pathway implemented in the Cardiology Department of a Chinese hospital. The results demonstrate that the approach, as a feasible solution to provide near real time conformance checking of CPs, not only enables clinicians to uncover non-compliant treatment behaviors, but also empowers clinicians with the capability to make informed decisions when dealing with treatment compliance violations in the pathway execution.

Determining Process Model Precision and Generalization with Weighted Artificial Negative Events

Process mining encompasses the research area which is concerned with knowledge discovery from event logs. One common process mining task focuses on conformance checking, comparing discovered or designed process models with actual real-life behavior as captured in event logs in order to assess the “goodness” of the process model. This paper introduces a novel conformance checking method to measure how well a process model performs in terms of precision and generalization with respect to the actual executions of a process as recorded in an event log. Our approach differs from related work in the sense that we apply the concept of so-called weighted artificial negative events toward conformance checking, leading to more robust results, especially when dealing with less complete event logs that only contain a subset of all possible process execution behavior. In addition, our technique offers a novel way to estimate a process model's ability to generalize. Existing literature has focused mainly on the fitness (recall) and precision (appropriateness) of process models, whereas generalization has been much more difficult to estimate. The described algorithms are implemented in a number of ProM plugins, and a Petri net conformance checking tool was developed to inspect process model conformance in a visual manner.