Systematic Mapping Study on Process Mining in Agile Software Development

dc.contributor.author Erdem, Sezen
dc.contributor.author Demirörs, Onur
dc.contributor.author Rabhi, Fethi
dc.coverage.doi 10.1007/978-3-030-00623-5_20
dc.date.accessioned 2018-12-13T11:35:42Z
dc.date.available 2018-12-13T11:35:42Z
dc.date.issued 2018
dc.description 18th International Conference on Software Process Improvement and Capability Determination, SPICE 2018; Tessaloniki; Greece; 9 October 2018 through 10 October 2018 en_US
dc.description.abstract Process mining is a process management technique that allows for the analysis of business processes based on the event logs and its aim is to discover, monitor and improve executed processes by extracting knowledge from event logs readily available in information systems. The popularity of agile software development methods has been increasing in the software development field over the last two decades and many software organizations develop software using agile methods. Process mining can provide complementary tools to Agile organizations for process management. Process mining can be used to discover agile processes followed by agile teams to establish the baselines and to determine the fidelity or they can be used to obtain feedback to improve agility. Despite the potential benefit of using process mining for agile software development, there is a lack of research that systematically analyzes the usage of process mining in agile software development. This paper presents a systematic mapping study on usage of process mining in agile software development approaches. The aim is to find out the usage areas of process mining in agile software development, explore commonly used algorithms, data sources, data collection mechanisms, analysis techniques and tools. The study has shown us that process mining is used in Agile software development especially for the purpose of process discovery from task tracking applications. We also observed that source code repositories are main data sources for process mining, a diversity of algorithms are used for analysis of collected data and ProM is the most widely used analysis tool for process mining. en_US
dc.identifier.citation Erdem, S., Demirörs, O., and Rabhi, F. (2018). Systematic mapping study on process mining in agile software development. In I. Stamelos, R. V. O'Connor, T. Rout, and A. Dorling (Eds.), Software Process Improvement and Capability Determination. SPICE 2018. Communications in Computer and Information Science, (pp. 289-299). Cham: Springer. doi:10.1007/978-3-030-00623-5_20 en_US
dc.identifier.doi 10.1007/978-3-030-00623-5_20
dc.identifier.doi 10.1007/978-3-030-00623-5_20 en_US
dc.identifier.isbn 978-3-030-00622-8
dc.identifier.scopus 2-s2.0-85054851587
dc.identifier.uri https://doi.org/10.1007/978-3-030-00623-5_20
dc.identifier.uri https://hdl.handle.net/11147/7042
dc.language.iso en en_US
dc.publisher Springer Verlag en_US
dc.relation.ispartof International Conference on Software Process Improvement and Capability Determination, SPICE 2018 en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Process mining en_US
dc.subject Agile software development en_US
dc.subject Process discovery en_US
dc.title Systematic Mapping Study on Process Mining in Agile Software Development en_US
dc.type Conference Object en_US
dspace.entity.type Publication
gdc.author.institutional Demirörs, Onur
gdc.author.yokid 167231
gdc.bip.impulseclass C5
gdc.bip.influenceclass C5
gdc.bip.popularityclass C4
gdc.coar.access open access
gdc.coar.type text::conference output
gdc.collaboration.industrial true
gdc.description.department İzmir Institute of Technology. Computer Engineering en_US
gdc.description.endpage 299 en_US
gdc.description.publicationcategory Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı en_US
gdc.description.scopusquality N/A
gdc.description.startpage 289 en_US
gdc.description.volume CCIS 918 en_US
gdc.description.wosquality N/A
gdc.identifier.openalex W2890943179
gdc.index.type Scopus
gdc.oaire.diamondjournal false
gdc.oaire.impulse 2.0
gdc.oaire.influence 3.3505196E-9
gdc.oaire.isgreen true
gdc.oaire.keywords anzsrc-for: 4609 Information Systems
gdc.oaire.keywords 4609 Information Systems
gdc.oaire.keywords anzsrc-for: 46 Information and Computing Sciences
gdc.oaire.keywords Process discovery
gdc.oaire.keywords 004
gdc.oaire.keywords 46 Information and Computing Sciences
gdc.oaire.keywords Networking and Information Technology R&D (NITRD)
gdc.oaire.keywords anzsrc-for: 4612 Software Engineering
gdc.oaire.keywords Process mining
gdc.oaire.keywords Agile software development
gdc.oaire.keywords 4612 Software Engineering
gdc.oaire.popularity 6.8775776E-9
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 02 engineering and technology
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.openalex.collaboration International
gdc.openalex.fwci 1.26864748
gdc.openalex.normalizedpercentile 0.8
gdc.openalex.toppercent TOP 10%
gdc.opencitations.count 6
gdc.plumx.crossrefcites 7
gdc.plumx.mendeley 50
gdc.plumx.scopuscites 14
gdc.scopus.citedcount 14
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relation.isOrgUnitOfPublication.latestForDiscovery 9af2b05f-28ac-4014-8abe-a4dfe192da5e

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