On the computation of Truck Factor
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Presentation at WETSOM 2012 workshop
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On the computation of Truck Factor
- 1. Is My Project’s Truck Factor Low? Theoretical and Empirical Considerations About the Truck Factor Threshold M. Torchiano, F. Ricca,A.Marchetto Presenter: M.Morisio
- 2. Agenda • What is the Truck-Factor? • What happens to TF in OSS projects? • When is TF low?
- 3. Truck Factor Bob Alice Joe Developers Files File 1 File 2 File 3 File 4
- 4. Truck Factor Bob Alice Joe File 1 File 2 File 3 File 4
- 5. Truck Factor Bob Alice Joe File 1 File 2 File 3 File 4 The remaining developers know 75% of the system (3 out of 4)
- 6. Truck Factor Bob Alice Joe File 1 File 2 File 3 File 4 The remaining developer knows just 50% of the system (2 out of 4)
- 7. Truck Factor • the number of developers on a team who have to be hit with a truck (i.e., to go on vacation, to become ill, or to leave the company for another) before the project is in serious trouble i.e. • before the remaining developers know less than T% of the modules
- 8. Which factors do influence TF? • Team size (n) • Residual knowledge threshold (T ) – Minimum Proportion of known files before reaching TF • Knowledge ratio (KR) – The average proportion of files known by each developer • Knowledge dispersion (σKR) – Standard deviation of KR
- 9. Sample projects 10 from Google code and 10 from Sourceforge
- 10. Project Fragility Threshold • A project is considered fragile when its TF is below a minimum threshold • Conjecture (Govindaray): – Small teams (n<10): 40% of team size – Large teams (n≥10): 20% ofteam size • In practice: – 16 out of 20 OSS projects are fragile – Only 4 are exactly at the threshold level
- 11. Maximum TF • Ideal condition: – Developers are split into two groups knowing KR ± σ of the system – Such knowledge is uniformly distributed among files • The maximum achievable TF is:
- 12. Maximum TF vs. Fragility Threshold
- 13. Conclusion • We compared the Govindaray threshold to the theoretical maximum TF: – the threshold appears either above the maximum or just barely below, i.e. practically unreachable • Real and healthy projects, when confronted with such metric, appear as fragile • Further work both empirical and theoretical is needed to define a fragility threshold applicable to real projects
Editor's Notes
- Good morning everybody, this work concerns theoretical and empirical considerations on the Truck Factor and was performed by Marco Torchiano, FilippoRicca and Alessandro Marchetto. Unfortunately they had to stay at home,… some one babysitting,… someone hard working, and someone else fishing.
- In this short presentation I will try to answer three main questions:…
- To understand what the Truck Factor is, we need to consider a typical software project where we find developers and files.Each file is know to a subset of developers, typically just a few.
- What happens if one of the developers leaves the project or has an accident?(he’s hit by a truck)Some files, known only to that unfortunate developer, become unknown for the project.
- The remaining developers collectively know just a fraction of the files.(A truck hits another developer)Some other file, known only to the second unfortunate developer become unknown.
- At this point the remaining team lost knowledge of most of the system
- [ Questa slide sipotrebbe non mostraree dare la definizionementresimostra la slide precedente ]
- Small projects have a large KR (required to know all the files) and tend to have more variabilityLarge projects tend to have small KR and smaller variability
- The conjecture has been presented in a blog post, there is no conventional publication reporting itThe four non-fragile projects have team size (n=3 or 4) therefore 40% = 1, and the actual TF is exactly equal to the threshold.
- [ la formula non èdacommentare, al limitesipotrebbesaltare la slide ]
- The maximum TF as a function of team size for different KR values at a fixed σKR = 0.1 (smaller than any real value)It is important to remember that the maximum TF can be obtained only with a perfectly uniform distribution of file knowledge among developers; actual projects are far from this condition.The continuous black line is the fragility threshold as proposed by GovindarayWe can observe how for large (n>10) projects and small KR (typical case) it is quite possible the project never pass the fragility threshold.