Wbma 2012

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)

Agenda� Motivation

� Research Objectives

� Methodology

� Research Contextualization

� Studied Cases

� Results

� Threats to validity

Motivations

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

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.

Research Objectives

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?

Methodology

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.

Context Research

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.

Studied Cases

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.

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.

Classification• According Cunnignham properties(1996)

Characterization and

conceptualization – Case 1

Results

Resulting Model: characterization

and e conceptualization of cases

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.

Results

(2) Strategic Decisions generated Technical Debt?

(3) What was the impact over time?

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.

Impacts

0

20

40

60

80

100

120

Upgrade JQuery Persistence MON CMDB

Delay in Delivery/Day

Contributions

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.

Threats to validity

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.

Questions?

Wbma 2012

Documents

Transcript of Wbma 2012