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Agile Business Rule Development. Process, Architecture, and JRules Examples. Bearbeitet von. Jérôme Boyer, Hafedh Mili. 1. Auflage Buch. xxvi, S. Request PDF on ResearchGate | Agile Business Rule Development | Target audience All; nontechnical audiences can skip Sects. and In this chapter you. Presentation covers all relevant aspects of the business rules approach: ISBN ; Digitally watermarked, DRM-free; Included format: PDF.
It still may be only partly achieved using sep- arate additionally developed software applications, which ensure automation and exe- cution of business processes responsible for decisions according to the business logics represented in BR. Boyer and Mili cater to different audiences: Kaunas University of Technology, Kaunas, pp. An approach for data analysis models integration. Vasilecas There are more problems left to solve in order to start a wide-ranging development of BR based intelligent ERP systems. LLC Houston.
All other company and product names are trademarks of their respective owners. Vasilecas for storing in BR repository and for processing in inference mechanism using logical operations described in the next section.
We propose to distinguish four main purposes of logical operations with BR that depend on the purpose and component used for such operations: At the moment there are several well-known logical derivation methods used in in- ference engines to process BR such as: Backward resolution also called goal-directed reasoning Kusiak, and Forward-Chaining also known as Data-Driven resoning Kusiak, , Rete inferencing algorithm Forgy, designed by Dr.
Charles Forgy during the late which found its way into expert system inferencing engines during the s and inferencing engines of BRMS nowadays, and Fuzzy logic Bremdal and Olsen, Backward resolution involves choosing hypothetical conclusions and test- ing to see if the necessary rules underlying the conclusions hold true and there are no contradictions in underlying rules.
This method is usually used for BR set consistency validation. However Flow engines using Neural networks Jain et al. This determines that logical operations with BR sets in modern systems are usually processed and enforced using the internal inference engine or so-called BRE of BRMS, which carries out various actions based on the reasoning results, e.
Such determined actions should be somehow executed in the software applications of dedicated ERP system. Such way of rule enforcement can be achieved in several ways: In Vasilecas and Smaizys we also discuss possibilities of different BR en- forcement level implementation in the software applications, because in some business scenarios such enforcement level may change depending on the business system state.
Rules in ERP packages usually cover basic business rules, but in case you have, for instance, a complex financial or legal scenario you would need to extend rules and enable flexible BR enforcement.
This could be allowed in Business rule based ERP systems, leading to the need of selection of corresponding architecture, components, techniques and tools.
On the base of our experience we could define the following different strategies and BR approaches based on ERP development maturity and used ERP engineering process complexity: Further in this section we will discuss all these approaches of BR based ERP system development and analyze their weak and strong sides according to the particular purposes. Vasilecas 4. Separate Development of Business Logic Model and Integration into the ERP System There are several ways of business rule enforcement and implementation into the final software system proposed: Usually this approach could be used for development of one particular component of ERP system, and achieved by separate development of static business logic model used in ERP system for execution of structured decisions using software system parameterisa- tion Casati et al.
This approach is similar and usually does not need the use of rule engine.
How- ever inference processing and involvement of some rule engine is useful for validation of BR combined into the rule sets used for further automated transformations.
Summarising our experience we could define two different alternatives of such BR enforcement and separately developed business logic model implementation in ERP systems: Parameter driven approach and Model transformation — driven ap- proach. For illustration of parameter driven approach in Smaizys and Vasilecas we have analysed decision automation based on BR represented as DT for use by separate components servicing in business logic layer dedicated for selection of action and execu- tion of related executable code in application layer or database layer of software systems.
The main difference of our approach is that for example ILOG uses separate Rule Execution Server and we dedicate this functionality to the separate software system com- ponent according to the SOA by automated generation of business layer objects and direct deployment of BR represented in DT to the Application database.
This approach is sim- pler and can be easy understand by IT people. Our approach is based on open source software and is inte- grated with Microsoft Visual Studio for the use by software developers. We argue that structured rules in DTs representing decisions required are simple and it is enough to automate development of querying process in the software system according to the BR managed at the business system level.
Although for more sophisticated and intelligent decision making methods based on statistical analysis e. Judging from the works of Avdejenkov et al. Our approach is related with the use of similar XML based source to destination meta-model based transformations with development of special transformation instructions stored as XML transformation schema Vasilecas and Smaizys, Another approach alternative to the business logic exchange achieved by centralization of business logic execution presented in the next section.
This approach has the additional advantage that the rules cannot be circumvented by operations on the DBMS because of triggers and stored pro- cedures are used for rule integration Badawy and Richta, However the business logic used in business processes is distributed through different information systems soft- ware and usually differs depending on technology used for each particular software sys- tem.
This leads to the problems dealing with inadequate automated decision processing and implementation of changes into different software or several parts of ERP system.
This can be avoided by using centralized business logic execution and BR enforcement in the integrated ERP system according to the framework presented in Avdejenkov et al.
The main advantage of this approach is that here the part of software dedicated to the business decisions together with the rules describing business logic is separated and implemented into the central component of BRMS. This component is responsible for business decisions and includes a model of decision propagation into the components of enterprise software through several available information system interfaces Fig.
The central part of proposed framework includes some reasoning processor for business rule execution. The Framework of integrated intelligent system using business rule management system. The interface to the external systems builds the communication between business users, internal BRMS system components and external software systems.
The emerg- ing agent software can be used for automation of BR discovery as well. The interface plays a key role in an open structured BRMS software system: BR based meta-rules concentration in one BRMS and rule exchange interfaces support intelligent interaction between different subsystems in an enterprise. Also, due to a flexible XML language used for BR formalization, it allows introducing an open organisation structure with a new intelligent functionality.
BRMS in this context allows not only integration of new services and business logic into the existing applications at the physical layer but also allows indirect integration of applications through BRMS or DBMS, as well Chorafas, ; Penya et al. According to our proposed framework, the integration possibilities are limited only by architecture of the application and functionality of external communication interfaces of DBMS and applications.
Intelligent Self Adaptable ERP Systems Nowadays information system development is experiencing transition from crisp logic to fuzzy logic.
This allows for both algorithmic and heuristic problem solving. Authors introduce fuzzy attributes, fuzzy constraints, and creation of FuzzyEER model with focus on semantic aspects in conceptual design Galindo et al. Fuzzy logic was defined in the late sixties of XXth century and enabled representation of more complicated rules with implication functions which were impossible using binary logic, e.
During our research we have challenged a few problems not discussed before related to the situations, when BR are not known at the beginning or they are incomplete even contradicting but we still need decisions. Moreover such BR systems are not static and should be changed when a business situation changes.
This means the need of develop- ment of the software systems that could be self adaptable to such changes and ensure information system adaptation to maximise achievement of goals dedicated by the execu- tive staff. Such situations may be resolved by involvement of fuzzy logic or flow engines implemented in BRMS component called BR mining engine. We have made some exper- iments for solution of such problem by building a risk model of Vasilecas and Smaizys Similarly in Graeme et al. Such approach allows dynamical adaptation of the user interface of the ERP application to the changes in business system observed from the collected enterprise data and generation of the business service and results in the extensions or modifications to the workflow logic, business logic or data logic being directly reflected in the operative user front-end and the presentation logic of ERP system.
Summarising intelligent features of ERP systems that we can get from the approaches described in previous sections — they usually are acting by structured rules and do not deal with every possible impact on the business environment or future consequences. Vasilecas the main reason why automated decisions based on such rules cannot take responsibility and requires involvement or approval of dedicated business people.
This limits decision automation possibilities. The use of fuzzy logic instead or together with crisp logic in ERP systems can be used to simulate a real business environment and evaluate possible impact providing automated heuristic decisions.
Discussions In this section we want to debate typical questions that may arise during discussions on the subject of this paper. We argue that there are not widely accepted standards or universal BR approach for ERP development yet. This leads to a large scale of different methods and variations of systems engineering processes and architectures used.
In this paper we have made efforts to group them into the three main groups according to the maturity level, complexity and components used to ensure the agile ERP system development. This started from a simple involvement of BR and separate man- agement according to the first approach described in Section 4. However this set is not final one and we expect new evolving methods of ERP systems develop- ment in the nearest future, especially those related to the intelligent self adaptable ERP systems.
Every further approach is more complicated and the selection of the approach used should be made according to the particular needs of ERP systems developers and business users. We agree that there are some limitations for modification of the existing data model. Especially, when using parameterisation approach in development process. However according to our method proposed in Smaizys and Vasilecas it is allowed to change the existing data model and we allow addition of new rules, conditions and actions, by propagating them directly into the data model of con- figuration part of the software representing BR based business logic by running automated transformations and executing DDL instructions in the new iteration of development process.
Automated refresh of logical model at the business system layer, update and automated generation refresh of the code at business logic tier according to the n-tier architecture is also required. However, we experienced lim- itation assuring compliance of already existing business data records to the new BR and still we can not deal with changes in existing attributes and relations of business entities being propagated in an automated way.
We agree that most of the presented information could be applied to the develop- ment of intellectualized IS in general. That is because as we have noticed before — the border between ERP systems and other kind of IS is going to be heavily distin- guished. However the ideas, methods and results presented in this paper are based on our running researches in the field of ERP systems only. Wider application of the methods presented in this paper for intellectualized IS in general should be produced with care and checked accordingly.
Conclusions In this paper we have overviewed BR based ERP systems engineering process and sepa- rated three main approaches used for such a ERP systems development based on maturity and complexity of engineering processes and methods used. Depending on the approach used for BR based ERP systems development it may be possible to ensure different level of agility by an instant deployment of changes in the Business policy and immediate reac- tion to the changes on the market or competition by changing existing business rules and introducing new rules not by programmers, but by business analysts.
Such advances al- low ERP systems to be more transparent, auditable and to achieve cost reduction because of more efficient process of introduction of changes in business policy into the software systems of BIS used for implementation of decision automation and decision support.
Current commercial ERP systems are developed using traditional BIS engineering methods and only few of them are on the first — BR separation level of maturity and complexity according to the BR based ERP approach classification proposed. Basically business rules are used only for description of business logics in business processes mod- elled and implemented in traditional way. Although BR based ERP systems have more complex development process in an ini- tial phases, but such a system is more efficient in further maintenance and simplified modifications that is especially needed for businesses with frequently changing regula- tions and business policy, competitive behaviour on the market and requiring a high level of customisation and adaptation to the large scale of separate customer needs, especially when the software is designed using SOA.
It still may be only partly achieved using sep- arate additionally developed software applications, which ensure automation and exe- cution of business processes responsible for decisions according to the business logics represented in BR.
Such extensions usually are integrated with ERP systems using all the available standard ERP system interfaces or special messages passed trough business process management server. Vasilecas There are more problems left to solve in order to start a wide-ranging development of BR based intelligent ERP systems.
Several early businesses oriented and ERP integrated products using business rules technology have their roots in the realm of artificial intelli- gence and inference systems. They were complex, expensive to run and maintain, and not business-user-friendly.
However some modern ERP system developers e. References Avdejenkov, V. Business rule management in enterprise resource planning systems.
IOS Press, pp. Badawy, M. Kirikova, M. Advances in Methodologies, Compo- nents and Management.
Bajec, M. A methodology and tool support for managing business rules in organisations. Information Systems, 30 6 , — Bocij, P. Business Information Systems. Pearson Education. Bremdal, B. An introduction to fuzzy systems in production and mechanical engineering. Wang, K. BRG Version 1. Ross, G. Version 2.
The business rules repository for information systems design. Research Communications, Vol. STU, Bratislava, pp.
Improving business rules management through the application of adaptive business intelligence technique. Information Technology and Control, 38 1 , 21— Casati, F. Adaptive and Dynamic Service Composi- tion in eFlow. HP Lab. Report, HPL Ceponiene, L. Information Technology and Control, 38 1 , 29— Chisholm, M.
The black box problem. Business Rules Journal, 3 3. How to Build a Business Rules Engine.
Morgan Kaufman Publishers. Chorafas, D. Operation management. Encyclopedia of Information Systems, Vol. Elsevier Science, pp. Ciuksys, D. Reusing ontological knowledge about business processes in IS engineering: Process configuration problem. Informatica, 18 4 , — Das, G. Rule discovery from time series.
AAAI Press, pp. Date, C.
What Not How: Reading, MA, Addison-Wesley. Eder, J. BIER — The behavior integrated entity-relationship approach. Spaccapietra, S. North-Holland, Amsterdam, pp. Eriksson, H-E. Business Modeling with UML: Business Patterns at Work. Forgy, C.
Artificial Intelligence, 19 1 , 17— Galindo, J. Fuzzy Databases: Modeling, Design, and Implementation. Graeme, S. Cam- bridge University Press. Grosof, B. Standardizing XML rules: Preece, A. Business Rules Applied: Hall, C. Requirement Analysis: From Business View to Architecture. Prentice-Hall, New Jersey. Hay, D. Guide Business Rule Project: Final Report.
Herbst, H. The specification of business rules: A comparison of selected methodologies.
Verrijn-Stuart, A. Elsevier, pp. Hossain, L. Enterprise Resource Planning: Idea Group Publishing. ILOG Jain, A. Data clustering: A review. JBoss Jess Kilov, H. Business patterns: Reusable abstract constructs for business specification. Humphreys, P. Concepts, Meth- ods and Experiences. Chapman and Hall, pp. Kusiak, A. Knowledge-based systems.
Kaunas University of Technology Press, Kaunas, pp. Loucopoulos, P. Modelling business rules in an office environment.
Mahajan, S. Oracle technical report. He is the leading developer of the first open source methodology for business rules: Agile Business Rule Development.
Buy Hardcover. Buy Softcover. FAQ Policy. About this book Business rules are everywhere. Show all. Pages Business Rules in Practice Boyer, Mr. Rule Harvesting Boyer, Mr. Prototyping and Design Boyer, Mr. Rule Engine Technology Boyer, Mr. Issues in Rule Authoring Boyer, Mr.
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