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Adam Tornhill on Good Engineering Culture, Technical Debt and Ways to Reduce Inter-Team Conflict

| Podcast with Adam Tornhill Follow 1 Followers by Shane Hastie Follow 9 Followers on May 15, 2017 |

This is the Engineering Culture Podcast, from the people behind InfoQ.com and the QCon conferences.

In this podcast Shane Hastie, InfoQ Lead Editor for Culture & Methods, spoke Adam Tornhill of Empear on combining psychology and software engineering, technical debt. 

Key Takeaways

  • The problems in software engineering are not technical they are almost always people related
  • A lot of technical debt is not actually technical in nature – it is due to organisational and social factors
  • Research that shows that the number of developers who work on a block of code is a predictor of the number of quality issues that code will have
  • There is a cuttoff point above which adding more people to work on a codebase becomes a negative return is fairly low
  • Safety to be able to admit to not knowing, collaboration and constant learning are key to a healthy engineering culture
  • Complex areas of a codebase which change frequently are the best targets for technical debt reduction - hotspots
  • Inter-team conflict is inevitable unless you have an engineering culture where there is a clear and compelling common goal

05m:10s Introductions

01m:10s Combining an interest in psychology with software engineering

01m:35s Exploring why it is so hard to build software

02m:00s The problems are not technical they are people factors

02m:25s Code is written by people and psychology is about how people work

02m:35s A lot of technical debt is not actually technical in nature – it is due to organisational and social factors

03m:20s We mistake organisational problems for technical issues

03m:50s A lot of code end up being written by many people over a number of years

04m:15s The more people who work on a part of the code the harder it is to build a stable long-term mental model of the codebase

04m:45s Research that shows that the number of developers who work on a block of code is a predictor of the number of quality issues that code will have

05m:05s While one-person, one codebase is the ideal it is also high risk and you need other techniques to overcome those risks

05m:20s Code reviews are vital for high quality code

05m:40s The conscious tradeoffs that need to be made between number of people working on a codebase and the risk of single point of failure

05m:45s There is a cuttoff point above which adding more people to work on a codebase becomes a negative return is fairly low

06m:10s Example of putting more people on a problem resulted in more than doubled the duration of the project

08m:00s Contrasting pair debugging and pair programming

08m:25s The research on pair programming was mainly done on university students, which is not a useful comparison for commercial development environments

08m:40s Some reasons why code reviews are valuable – defect identification & reduction, social pressure to be more careful and knowledge sharing

09m:55s Build peer review into the engineering culture of the organisation

10m:45s What makes a productive engineering culture

10m:55s Safety to be able to admit to not knowing and to make mistakes

11m:05s Collaboration and constant learning are key to a healthy engineering culture

11m:35s To encourage a good engineering culture the leader needs to model the behaviours you want to see

11m:45s The leader’s responsibility to remove obstacles

12m:00s What is the process for buying a book?  If it requires authorisation and approval then the organisation doesn’t really have a learning culture

12m:35s The ways the term technical debt is misused

13m:01s Just because some code is bad (or you don’t like how it was written) doesn’t make it technical debt – it’s only technical debt if we have to pay interest on it (it needs to be changed)

13m:35s Prioritise the technical debt you really need to fix

13m:50s Technical debt has a time dimension – a block of bad code which works and doesn’t need changing shouldn’t be prioritised

14m:50s There are some parts of any codebase that need to be changed frequently, technical debt in these areas matters

15m:10s Pareto principle in defect density

15m:45s Mine the version control history to see which parts of the code base change frequently and prioritise work around them – probably 4-5% of the codebase

16m:30s Add complexity as a second dimension; complex areas which change frequently are the best targets for technical debt reduction - hotspots

17m:20s Find the reason for an area of code becoming a hotspot

17m:30s Low cohesion is the number one reason that code becomes a hotspot

17m:40s Poorly understood domain concepts lead to lots of churn in the code that implements them

18m:00s These are problems which we know how to fix, in practice the level of churn makes it hard to simplify the code

18m:40s You need to consider the organisation social perspective as you refactor code

19m:10s Conways law and Brooks Law still apply

20m:10s Conway’s law drives us to separate concerns, however there is a price to be paid in inter-team conflicts

21m:00s Exploring how churn in the codebase can be visible evidence of inter-team conflict

21m:15s The information in the version control system exposes the social aspects of team collaboration

21m:50s Inter-team conflict is inevitable unless you have an engineering culture where there is a clear and compelling common goal

22m:35s The motivational value of knowing how your contribution fits into the bigger picture

23m:25s Build a culture where people care about what they build, and encourage learning 

23m:45s Put numbers on your technical debt – don’t rely on gut feelings 

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