Mining Project-Oriented Business Processes

Mining Project-Oriented Business
Processes
Saimir Bala, Cristina Cabanillas, Jan Mendling,
Andreas Rogge-Solti, Axel Polleres

Motivation
Imagine a train crashes because of an engineering error and
a lot of people get injured
You are a national railway system administrator, say ABC
You might be in trouble!
Mining Project-Oriented Business Processes Motivation 2 / 22

Agenda
Problem
Project-Oriented Business Processes
Approach
Conclusion
Mining Project-Oriented Business Processes Motivation 3 / 22

Agenda
Problem
Approach
Conclusion
Mining Project-Oriented Business Processes Problem 4 / 22

Who is responsible?
Are you as ABC responsible for the accident?!
Show that your work complies with safety regulations
E.g. in the railway domain EN50128, EN50129, EN50126

How to provide evidence of compliance?
Analyze the work in retrospect
The company does not use a BPM engine to execute their processes:
No process designed a priori
Rather a project that is handled ad-hoc by engineers
An expert (auditor) analyses the existing documentation and
manually checks if everything was done properly
Spreadsheets, wordprocessor, diagrams, version control system (VCS)
data

Agenda
Problem
Approach
Conclusion
Mining Project-Oriented Business Processes Project-Oriented Business Processes 7 / 22

Idea: mine project-oriented business pro-
cesses
Has the accident something to do with the software?

Classic business process Project-oriented business process
Engine No engine
Recursive, cyclic One time with ﬁxed goals and resources
Many instances One prototype/product
Process model (e.g. BPMN) Plan (e.g. GANTT chart)
Activities Workpackages
Subprocesses Subworkpackages

Classic business process Project-oriented business process
Engine No engine
Recursive, cyclic One time with ﬁxed goals and resources
Many instances One prototype/product
Process model (e.g. BPMN) Plan (e.g. GANTT chart)
Activities Workpackages
Subprocesses Subworkpackages
Process mining

State of the art: reduction to process min-
ing
Mining a process from software repositories (Kindler et al.,2006)

State of the art: visualization I
Dotted chart (Song & van der Aalst,2007)

State of the art: visualization II
Storylines (Ogawa & Ma, 2010)

Agenda
Problem
Approach
Conclusion
Mining Project-Oriented Business Processes Approach 13 / 22

Mining VCS logs
Input: VCS logs (e.g. from Git, Subversion, etc)
Output: GANTT chart

Challenges
Timing (how big is the activity in reality wrt to what we see in the
log?)
Aggregation (how can we aggregate events into activities? and how
can we see the project from a coarser grained point of view?)
Coverage (how eﬃciently was the time used?)

Assumptions

Assumptions
1. Meaningful tree structure

Assumptions
2. Members perform local changes

Assumptions
2. Members perform local changes
3. Systematic commits

Visualization of a project
Aggregation (data from the SHAPE-project)
Time span Jan 2014 – Jan 2015
8 people
156 objects (ﬁles and directories)
226 commits, generating 453 events

Correction of activity starting times
Adjustment and coverage

Evaluation on open source projects
Log Duration Idle periods Files Commits ˆtc χ
File name Days Number Number Number Hours %
Our work 24 0 89 63 9 100
Whitehall 1279 6 6539 15566 2 95
Petitions 834 17 1562 914 13 59
Study 624 13 7501 736 11 58
The Guardian 1667 59 12889 621 30 44
Book 414 15 154 592 5 32
Papers 1859 55 1791 649 20 30
Requirements 771 22 505 231 17 21
Yelp 206 6 24 54 20 20
Adobe 1076 13 356 237 24 15
More real world logs on https://github.com/showcases

Limitations and Future work
Limitations
Strong assumptions on the structure
The approach doesn’t take into account amount of documents
changes
Checking rules
Future work
Use statistic methods to improve the quality of the discovered projects
Discover the type of work/project by using comments written by users
User assessment of the quality of the discovered GANTT charts

Agenda
Problem
Approach
Conclusion
Mining Project-Oriented Business Processes Conclusion 21 / 22

Conclusion
We help the auditor to analyze the project
Diﬀerent levels of abstraction (aggregation)
Time and resource of events
Work eﬀort measure (coverage)
We used project VCS logs
Output as GANTT chart
Source code: https://github.com/s41m1r/MiningCVS
Email me: saimir.bala@wu.ac.at
Mining Project-Oriented Business Processes Conclusion 22 / 22

References
Kindler, E., Rubin, V. & Schäfer, W. (2006). Activity Mining for
Discovering Software Process Models. Software Engineering 79,
175–180.
Ogawa, M. & Ma, K.-L. (2010). Software evolution storylines. In
Proceedings of the 5th international symposium on Software
visualization (pp. 35–42).
Song, M. & van der Aalst, W. M. (2007). Supporting process mining
by showing events at a glance. In 7th Annual Workshop on
Information Technologies and Systems (pp. 139–145).
Baier, T., Mendling, J., & Weske, M. (2014). Bridging abstraction
layers in process mining. Information Systems, 46, 123-139.
Part I: AppendixMining Project-Oriented Business Processes References 1 / 4

Expected active time between commits
Expected active time between commits ^tc is given as follows.
(1) ^tc =
a∈Af
(ω(a) − α (a))
a∈Af
(c(a) − 1)
with
ω (a): End time of activity a
α’(a): Time of the ﬁrst event of the activity a
c (a): Number of commits in activity a
Part I: AppendixMining Project-Oriented Business Processes Backup 2 / 4

Coverage factor
Deﬁnition (Coverage)
The coverage χ of work packages by activities is a function χ : W → [0, 1]
and is deﬁned as follows.
(2) χ(w) =
a∈β−1(w) (ω(a) − α(a))
τ(w)
where τ is the duration of work package w.

Average idle time
Let nc be the number of commits per work package. We compute the
average idle time as follows.
(3) tIdle =
τ − nc ·^tc
n
, n > 0
where n is the number of idle times in the work package, and τ is the time
duration of the work package.

Mining Project-Oriented Business Processes

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