Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Towards Intent-Driven Systems
Blekinge Institute of Technology, Faculty of Computing, Department of Software Engineering.ORCID iD: 0000-0003-0396-1993
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Context: Software supporting an enterprise’s business, also known as a business support system, needs to support the correlation of activities between actors as well as influence the activities based on knowledge about the value networks in which the enterprise acts. This can be supported with the help of intent-driven systems. The aim of intent-driven systems is to capture stakeholders’ intents and transform these into a form that enables computer processing of them. Only then are different machine actors able to negotiate with each other on behalf of their respective stakeholders and their intents, and suggest a mutually beneficial agreement.

Objective: When building a business support system it is critical to separate the business model of the business support system itself from the business models used by the enterprise which is using the business support system. The core idea of intent-driven systems is the possibility to change behavior of the system itself, based on stakeholder intents. This requires a separation of concerns between the parts of the system used to execute the stakeholder business, and the parts which are used to design the business based on stakeholder intents. The business studio is a software that supports the realization of business models used by the enterprise by configuring the capabilities provided by the business support system. The aim is to find out how we can support the design of a business studio which is based on intent-driven systems.

Method: We are using the design science framework as our research frame- work. During our design science study we have used the following research methods: systematic literature review, case study, quasi experiment, and action research.

Results: We have produced two design artifacts as a start to be able to support the design of a business studio. These artifacts are the models and quasi-experiment in Chapter 3, and the action research in Chapter 4. The models found during the case study have proved to be a valuable artifact for the stakeholder. The results from the quasi-experiment and the action research are seen as new problem solving knowledge by the stakeholder.

Conclusion: The synthesis shows a need for further research regarding semantic interchange of information, actor interaction in intent-driven systems, and the governance of intent-driven systems.

Place, publisher, year, edition, pages
Karlskrona: Blekinge Tekniska Högskola, 2017. , 129 p.
Series
Blekinge Institute of Technology Licentiate Dissertation Series, ISSN 1650-2140 ; 1
Keyword [en]
business intent, business support system, intent-driven system, compositional system
National Category
Software Engineering
Identifiers
URN: urn:nbn:se:bth-15141ISBN: 978-91-7295-342-0 (print)OAI: oai:DiVA.org:bth-15141DiVA: diva2:1141763
Opponent
Supervisors
Projects
Professional Licentiate of Engineering Research School
Funder
Knowledge Foundation
Available from: 2017-09-22 Created: 2017-09-15 Last updated: 2017-09-22Bibliographically approved
List of papers
1. A Systematic Literature Review on Intent-Driven Systems
Open this publication in new window or tab >>A Systematic Literature Review on Intent-Driven Systems
(English)In: Article in journal (Refereed) Submitted
Abstract [en]

Context: The aim of intent-driven systems is to capture stakeholders’ intents and transform these into a form that enables computer processing of the intents. Only then are different computer- based agents able to negotiate with each other on behalf of their respective stakeholders and their intents, and suggest a mutually beneficial agreement. This requires a separation of concerns between the parts of the system used to execute the stakeholder business, and the parts which are used to design the business based on stakeholder intents.

Objective: The aim is to find out which methods/techniques as well as enabling aspects, useful for an intent-driven system, that are covered by research literature.

Method: As a part of a design science study, a Systematic Literature Review is conducted.

Results: The existence of methods/techniques which can be used as building blocks to construct intent-driven systems exist in the literature. How these methods/techniques can interact with the aspects needed to enabling flexible realizations of intent-driven systems is not evident in the existing literature.

Conclusion: The synthesis shows a need for further research regarding semantic interchange of information, actor interaction in intent-driven systems, and the governance of intent-driven systems.

Keyword
business intent, business support system, intent-driven system, systematic literature review
National Category
Computer Science
Identifiers
urn:nbn:se:bth-15171 (URN)
Available from: 2017-09-21 Created: 2017-09-21 Last updated: 2017-09-25Bibliographically approved
2. Supporting Continuous Changes to Business Intents
Open this publication in new window or tab >>Supporting Continuous Changes to Business Intents
(English)In: International journal of software engineering and knowledge engineering, ISSN 0218-1940Article in journal (Refereed) Accepted
Abstract [en]

Context: Software supporting an enterprise’s business, also known as a business support system, needs to support the correlation of activities between actors as well as influence the activities based on knowledge about the value networks in which the enterprise acts. This requires the use of policies and rules to guide or enforce the execution of strategies or tactics within an enterprise as well as in collaborations between enterprises. With the help of policies and rules, an enterprise is able to capture an actor’s intent in its business support system, and act according to this intent on behalf of the actor. Since the value networks an enterprise is part of will change over time the business intents’ life cycle states might change. Achieving the changes in an effective and efficient way requires knowledge about the affected intents and the correlation between intents.

Objective: The aim of the study is to identify how a business support system can support continuous changes to business intents. The first step is to find a theoretical model which serves as a foundation for intent-driven systems.

Method: We conducted a case study using a focus group approach with employees from Ericsson. This case study was influenced by the spiral case study process.

Results: The study resulted in a model supporting continuous definition and execution of an enterprise. The model is divided into three layers; Define, Execute, and a com- mon governance view layer. This makes it possible to support continuous definition and execution of business intents and to identify the actors needed to support the business intents’ life cycles. This model is supported by a meta-model for capturing information into viewpoints.

Conclusion: The research question is addressed by suggesting a solution supporting con- tinuous definition and execution of an enterprise as a model of value architecture compo- nents and business functions. The results will affect how Ericsson will build the business studio for their next generation business support systems.

Keyword
business intent; actor; viewpoint; business support system; intent-driven sys- tem; context frame; compositional system; knowledge creation; case study; continuous change
National Category
Computer Science
Identifiers
urn:nbn:se:bth-15172 (URN)
Available from: 2017-09-21 Created: 2017-09-21 Last updated: 2017-09-25Bibliographically approved
3. Encouraging Business Flexibility by Improved Context Descriptions
Open this publication in new window or tab >>Encouraging Business Flexibility by Improved Context Descriptions
2017 (English)In: Proceedings of the Seventh International Symposium on Business Modeling and Software Design / [ed] Boris Shishkov, SciTePress, 2017, Vol. 1, 225-228 p.Conference paper, Published paper (Refereed)
Abstract [en]

Business-driven software architectures are emerging and gaining importance for many industries. As softwareintensive solutions continue to be more complex and operate in rapidly changing environments, there is a pressure for increased business flexibility realized by more efficient software architecture mechanisms to keep up with the necessary speed of change. We investigate how improved context descriptions could be implemented in software components, and support important software development practices like business modeling and requirement engineering. This paper proposes context descriptions as an architectural support for improving the connection between business flexibility and software components. We provide initial results regarding software architectural mechanisms which can support context descriptions as well as the context description’s support for business-driven software architecture, and the business flexibility demanded by the business ecosystems.

Place, publisher, year, edition, pages
SciTePress, 2017
Keyword
Context Description, Business Flexibility, Business Support System, Requirements Engineering, Business Model
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:bth-15147 (URN)10.5220/0006529300000000 (DOI)978-989-758-238-7 (ISBN)
Conference
Eight International Symposium on Business Modeling and Software Design, BMSD, Barcelona
Available from: 2017-09-19 Created: 2017-09-19 Last updated: 2017-09-25Bibliographically approved
4. Towards Executable Business Rules
Open this publication in new window or tab >>Towards Executable Business Rules
2017 (English)Other (Refereed)
Abstract [en]

Context:  In today's implementations of business support systems, business rules are configured in different places of the system, and in different formats. This makes it hard to have a common view of what is defined, and to execute the same logic in different parts of systems. It is desired to have a common governance structure and a standardized way of handling the business rules.

Objective: To investigate if it is possible to support visual and logical verification of business rules and to generate executable business rules.

Method: Together with practitioners we conducted an experiment.

Results: We have implemented a machine learning pipe-line which supports visual and logical verification of business rules, and the generation of executable business rules. From a machine learning perspective, we have added the possibility for the ID3 algorithm to use continuous features.

Conclusion: The experiment shows that it is possible to support visual and logical verification of business rules, and to generate executable business rules with the help of a machine learning pipe-line.

Keyword
business intent; business support system; business rules; decision tree
National Category
Computer Science
Identifiers
urn:nbn:se:bth-15175 (URN)
Note

Accepted as an Appendix.

Available from: 2017-09-21 Created: 2017-09-21 Last updated: 2017-09-25Bibliographically approved
5. Uncovering Implicit Rules in Medicine Diagnosis
Open this publication in new window or tab >>Uncovering Implicit Rules in Medicine Diagnosis
(English)In: Article in journal (Refereed) Submitted
Abstract [en]

Context:  Decisions taken by experts may be based on explicit and implicit rules. By uncovering the implicit rules the expert may have the possibility to explain its decisions in a better way, both for itself and the person which the decision is affecting. In the area of medicine, laws are enforcing the expert to be able to explain its decision when a patient is complaining about a decision. Another vital aspect is the ability of the expert to explain to the patient why a certain decision is taken, and the risks associated with the decision.

Objective: To investigate if it is possible for a machine learning pipe-line to find implicit rules used by experts, when they decide if a patient could be operated or not.

Method: We conduct an analysis of a data set, containing information about patients and the decision if an operation should be performed or not.

Results: We have implemented a machine learning pipe-line which supports detection of implicit rules in a data set. The detection of the implicit rules are supported by an algorithm which implements an agglomerative merging of feature values. We have improved the original algorithm by showing the boarders of the feature values of a discretization bin.

Conclusion: The analysis of the data set shows it is possible to find implicit rules used by the experts with the help of an agglomerative merging of feature values.

Keyword
agglomerative feature value merging; implicit rules detection; decision tree
National Category
Computer Science
Identifiers
urn:nbn:se:bth-15179 (URN)
Available from: 2017-09-22 Created: 2017-09-22 Last updated: 2017-09-25Bibliographically approved

Open Access in DiVA

fulltext(777 kB)109 downloads
File information
File name FULLTEXT01.pdfFile size 777 kBChecksum SHA-512
8f3dd79fa4f4e0de810894b7fe54fe31b918644bdc59da94eb806fa985608e9746302f752d71a3a327c507ff9620d850760cc26aa54cb26a75f3580cc5123fee
Type fulltextMimetype application/pdf

Search in DiVA

By author/editor
Silvander, Johan
By organisation
Department of Software Engineering
Software Engineering

Search outside of DiVA

GoogleGoogle Scholar
Total: 109 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Total: 114 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf