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IBM Software Group
Timeboxes in a New Paradigm
of Behavior Modeling
Barclay Brown, ESEP
IBM
barclayb@us.ibm.com
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Behavior
 Behavior of organizations and systems is modeled in various ways
 Behavior refers to the activities of organizations and technological
systems, and their interactions
 What is referred to as behavior here has also been described as:
Organizational behavior
Business processes
System functional flow
Organization
System
Activity Flow
Task procedures
Organization
Use case flow of events
Operational scenarios
Concept of Operations (CONOPS)
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Two Paradigms
 Two primary paradigms, the process paradigm and the
systems paradigm.
Process paradigm: behavior is described in processes, which
consist of sequences of activities.
Systems paradigm, behavior is described as sequences of activities
and interactions between systems, sub-systems and users, in order
to achieve a user goal.
New
Energy
Policy
Process
Claim
Form
Detect
Target
Order a
Book
Online
Brighten
Screen in
Sunlight
Levels of
Abstraction
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A Personal Example
A complex system
Complex system interaction
 How to model a life?
Processes?
 A day in the life
 Career, family, hobby processes?
Use Cases?
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Complex systems using technology
“The unexamined
[unmodeled?] life is
not worth living”
- Socrates
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Key Concept:
Time and Sequence
 The key to untangling and understanding
complex processes is the representation of
time.
 Time = Past + Present + Future
The past looks linear, like a timeline
The present looks simultaneous, like a process
The future looks timeboxed, like a plan
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Past, Present and Future
PRESENT
TIMELINE
 Past events are easy to see on a linear timeline (we know when they
happened)
 A process can be seen as happening now, in the present (but of
course this isn’t really true—the present is of infinitesimally short
duration, so nothing actually happens in the present)
 The future really contains processes contained in timeboxes
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An Example:
he Heart’s Past,
Present and Future
PAST
FUTURE
PRESENT
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Timelines: A natural view of time
http://www.scientificamerican.com/article/space-shuttle-retirement-timeline/
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Timeboxes
• Boxes of time
• Have start time, end time and duration
– Any or all of these may be unknown
• All start/end dates/times are ranges
– 11/11/13 means the 24 hour period starting at midnight
– 3:05pm means the 60 second period starting 3:05:00 (or
3:04:31?)
– Q2 means the 90 day period beginning April 1.
• Durations ideally also include uncertainty
–
–
–
–
Best case: 2 hours
Worst case: 5 hours
Most likely case: 3 hours
Triangular distribution used to express estimates
• Actual outcome has skewed distribution (more often late then early)
• Timeboxes “connect” to each other only in time
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Timebox Examples
Implement Interface by Friday
RFP Response Q2-Q3
2-4 hours
Q2
July 1,
00:00:00
Sep 30,
23:59:59
Q3
?
Friday
Timeboxes on a timeline
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Timeboxes with Timelines Examples (cont’d)
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Ongoing Processes
ABSTRACT TIMELINE
 Indeterminate start, end and duration
 Shows relative time positioning
 Allows for zooming in and out in modeling tools
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Nesting/Recursion in Timeboxes
 A timebox may contain other timeboxes
 A timebox may contain a timeline or not.
 If a timebox does contain a timeline, the timeline must synchronize with all other timelines
 If it does not, then contained timeboxes are simply grouped and assumed to all occur
within the interval of the containing timebox.
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Benefits of Timeboxes in Behaviour modelling
 Processes can be shown in relation to the passage of time, without committing
individual process elements to specific points in time.
 Iterative and conditional process flows can be shown where they are planned to
occur in time, without reducing them to a series of specific events and activities.
 Processes can be shown as related to each other in time without implying
causal relationships and direct connections.
 The difference between past, present and future events and activities, is
incorporated in a single model. Planned (future) activities flow seamlessly into the
past as uncertainty is eliminated.
 Enough information about the uncertainty of timing is included that overall
behavioural models can be constructed and simulated using Monte Carlo and
other simulation techniques.
 Variable precision--start, end and duration times can be expressed in scales of
seconds, minutes, days, months or years. (Zooming in and out in time can be
automated in graphical tools.)
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