Paper: Tracking Technical Debt- An Exploratory Case Study Authors: Yuepu Guo, Carolyn Seaman, Rebeka Gomes, Antonio Cavalcanti, Graziela Tonin, Fabio Q. B. Da Silva, André L. M. Santos, Clauirton Siebra Session: Early Research Achievement Track Session 3

1. ICSM 2011
Williamsburg,VA, USA
May 25 – May 30, 2011
Tracking Technical Debt
— An Exploratory Case Study
Yuepu Guo, Carolyn Seaman
Information Systems Department, University of Maryland Baltimore County, USA
Rebeka Gomes, Antonio Cavalcanti, Graziela Tonin, Fabio
Q. B. Da Silva, André L. M. Santos, Clauirton Siebra
CIn/UFPE - Center of Informatics at Federal University of Pernambuco, Brazil

2. Introduction
 Technical Debt
 Delaying software maintenance tasks for short term gain but possible long term cost
 Risk – additional cost (interest) and uncertainty of interest payment
 Decision – what technical debt should be paid off and when?
 Management Practice
 IMPLICIT technical debt management
 Experience-based decision making (no rigorous measurement)
 Proposed Research
 Cost-benefit relationships of incurring technical debt
 Costs and benefits of EXPLICIT technical debt management
 Retrospective study
 Research Questions
 How and to what extent technical debt affects software projects?
 Is the decision simulation is effective to uncover the benefits of explicit technical debt
management?
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3. Background
 Larger Research Project
 Measuring and Monitoring Technical Debt
 Technical Debt Management Framework
ID 20
Date TD
7/18/2009
Measurement
Responsible Rose Angel
Type TD Documentation TD
Location Identification Module S Monitoring
Description In the last release, function F was added to
TD
module S, but the documentation has not
been updated to reflect this change.
Principal List
3.5 person-day
Interest Amount: 1.5 person-day
Interest Probability 40%
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4. Subject Technical Debt Item
 System
 Software application from a multi-national company
 Client solution for Microsoft Exchange Server
 63,218 LOC and over 5 years of evolution with 20 developers involved
D1 D3
 Evolution D2
R1 R2
Cost X
2011
 D1: Decision to maintain WebDAV communication protocol
D1: Decision to maintain WebDAV protocol
 D2: Decision to couple persistenceand communication layers
D2: Decision to coupple persistence
and communication layers
D3: Decision to support MS Exchange 2007
 D3: Decision to upgrade to ActiveSync communication protocol
R1: First system release
R2: First maintenance release
 R1: First system release
 R2: Second system release
 Technical Debt Item
 Delayed change of the communication protocol (T1)
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5. Methodology
 Measurement
 Technical debt item (T1)
 Principal: Effort to switch to ActiveSync (new protocol)
 Interest Amount: Rework effort on affected modules
 Interest Probability
 Coupling the communication and persistence layers
 Switching to ActiveSync
 Impact of T1
 Gain: Principal
 Loss: Interest Amount × Interest Probability
 Decision Simulation Process
Estimate
Track TD item Simulate Compare
principal and
at D1 decision decisions
interest
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6. Results
 Decisions D1 D2 D3
Actual
Defer Defer Defer
Decision
Simulated
Pay Pay Pay
Decision
 Simulated Cost/Benefit Analysis The value of explicit
technical debt management
1000 929
800
Labor-hour
585
600 507 507 507
400
Beneift
Cost
200
65
0
D1 D2 D3
6 Decision Point

7. Conclusion
 Technical debt may have significant impact on software
projects (tripled the development cost in this case)
 A decision made without careful analysis could
aggravate the negative effect of technical debt
 Explicit management of technical debt could prevent
high cost incurred by technical debt
 Decision simulation provides an effective approach to
the technical debt problem
 Business factors
 Real benefit of incurring the technical debt
 Over-simplicity of the approach
 Multi-disciplinary team
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8. Questions?
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