wbma 2012
TRANSCRIPT
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Graziela S. Tonin¹, Rogério Chaves², Alfredo Goldman¹, Viviane Santos¹.
Instituto de Matemática Estatística e Ciência da Computação – Universidade de São Paulo (USP).
² Instituto de Pesquisas Tecnológicas do Estado de São Paulo (IPT)
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Agenda� Motivation
� Research Objectives
� Methodology
� Research Contextualization
� Studied Cases
� Results
� Threats to validity
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Motivations
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Motivations� Techinical Debt
“Shipping first time code is like going into a debt. A little debt speeds development so long as it is paid back promptly with a rewrite. Objects
make the cost of this transaction tolerable. The dangers occurs when the debt is not repaid. Every minute spent on not-quite-right counts as interest on that
debt...”
Cunningham (1992)
� Gartner (2012)
� Technical Debt cost in 2010 was approximately $ 500 billion
� 2015 : The cost will reach U$1 trillion
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Motivations� Increased the adoption of Agile Methods in the last 10 years.
(VersionOne 2012 e Williams 2010).
� Effectiveness and benefits have been significant:
� More productive teams .
� Less Stress.
� Customers more satisfied with the products delivered.
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Research Objectives
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Research Objectives
(1) The Technical Debt concept is known in the company?
� If yes, how is considered in project management?
(2) Strategic Decisions generated Technical Debt?
(3) What was the impact over time?
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Methodology
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Methodology� Exploratory case study
� Selected based on purposive sampling method. [Yin, 2010]
� Data collected through interviews.
� Open and close questions.
� Interviews of the 30 minutes.
� Five people interviewed.
� Focus on historical project.
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Context Research
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Context Research� Project conducted in a technology company with more
than 350 developers and 45 Scrum teams.
� Project: Monitoring and automation system, developed in java with more than 100,000 lines of code.
� Four cases studied.
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Studied Cases
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Studied Cases� Case 1
� Upgrade of the JQuery version.� Fix system bugs.
� New features.
� Case 2� Persistence method of monitoring events in the
database.� Scalability limitation.
� Thousands devices monitored.
� Monitored only status changes.
� Metrics collected in the monitoring agents not persisted.
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Studied Cases� Case 3
� Use of MON (https://mon.wiki.kernel.org/) as monitoring agent.
� Monitor service availability.
� Case 4
� CMDB (Configuration Management Database) as mandatory data insertion in the system.
� System for configuration management.
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Classification• According Cunnignham properties(1996)
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Characterization and
conceptualization – Case 1
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Characterization and
conceptualization – Case 2
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Characterization and
conceptualization – Case 3
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Characterization and
conceptualization – Case 4
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Results
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Resulting Model: characterization
and e conceptualization of cases
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Results(1) The Technical Debt concept is known in the company? If yes, how is considered in project management?
� The company had knowledge.
� But not considered in project management.
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Results
(2) Strategic Decisions generated Technical Debt?
(3) What was the impact over time?
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Analysis of impacts in the Cases� Case 2, Case 3 and Case 4
� Process Adjustment.
� Business adapting to the system.
� All cases
� Rewrite code.
� Team division:
� Maintain an old system.
� Develop new solution.
� High level of stress – customer and project team
� Customer dissatisfied.
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Impacts
0
20
40
60
80
100
120
Upgrade JQuery Persistence MON CMDB
Delay in Delivery/Day
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Contributions
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Contributions� Confirms the importance of not ignoring Technical
Debt.
� Highlights the importance of communication between technical and business team.
� General Model that may help to show:
� Where Techincal Debt arise;
� What are your influences and motivations;
� Can be considered at the moment of decision-making.
� Can be replicated in other projects.
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Threats to validity
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Threats to validity� Data collected only through interviews.
� Data triangulation.
� Don’t have a detailed calculation of impact / cost.
� No data access as:
� Man/hour value.
� Cost of maintaining the old system while the new version was made.
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Questions?