Friday, May 4, 2018

Why should start-ups care about technical debt?

By: Eriks KlotinsBlekinge Institute of Technolgy
Associate Editor: Mehdi Mirakhorli (@MehdiMirakhorli)

We asked 84 start-ups to estimate levels of technical debt (TD) in their products and reflect on their software engineering practices. Technical debt is a metaphor to describe suboptimal solutions arising from a tradeoff between time-to-market, resources, and quality. When not addressed, compound effects of suboptimal solutions hinder further product development and reduce overall quality. 
Start-ups are known for their speed of developing innovative products and entering new markets. Technical debt can slow a start-up down and hinder its potential of quickly iterating ideas, or launching modifications for new markets. On the upper side, start-ups can leverage on technical debt to quickly get a product out to customers without significant upfront investment in product development.

Our data from 84 companies shows a clear association between excessive levels of technical debt and state of start-ups. We differentiate between active start-ups working on their products, and closed and paused start-ups. The results show that too much technical debt can impair product quality to the extent that further investments in the product to remove technical debt become unfeasible. Thus, excessive technical debt can kill the product and the company. Also, sustaining high levels of technical debt harms teams' morale as a lot of time is spent on patching the product. We are not advocating for the removal of all technical debt. Instead, we advocate for more understanding and awareness of technical debt.

1- Learn how to spot technical debt

Technical debt can affect different product artifacts, such as source code, documentation, architecture, documentation, and infrastructure.

Code debt or code smells correspond to poorly written code, such as unnecessary code duplication and complexity, long methods/functions, bad style reducing readability. Code debt is the easiest to spot.

Documentation debt refers to shortcomings in distributing knowledge on how to evolve, operate, and maintain the product. For example, poorly documented requirements, outdated architecture drawings, and lack of instructions what maintenance actions are required falls into this category. Documentation can be white-board drawings, notes, information in on-line tools, and formal documents. In start-ups lack of documentation is often compensated by implicit knowledge about the product. However, when team grows, key people may leave or the product may be transferred to another team, e.g., in case of an acquisition, perceived level of documentation debt peaks. The new engineers need to spend a significant effort to learn the product.

Architecture debt concerns structure of the software with effects on its maintainability and adaptability. Start-ups often use open-source frameworks and components to construct their products. Typically, popular frameworks come with their own best practices, and following these practices assures compatibility, easy to upgrade, and makes onboarding of new engineers faster.

Testing debt refers to lack of test automation leading to the need to manually test an entire product before every release. With lack of automation, an effort of regression testing grows with every new feature, supported platform and configuration. Regression testing could not be a problem while a product is small, however, testing debt could become a concern later as start-up matures and needs to support an increasing number of features across multiple platforms.

Environmental debt concerns hardware, other supporting applications, and processes relevant for development, operation and maintenance of the software product. For example, outdated server software leading to security vulnerabilities. Lack of data backup routines, problems in versioning, shortcomings in defect management, and other inadequacies may affect team's ability to create a quality product.

2- Main causes of technical debt

We found that level of engineering skills and the size of the whole start-up team are the primary causes of excessive technical debt. Inexperienced developers are more likely to unknowingly introduce technical debt. Our analysis shows that lack of skills contributes to communication issues and shortcomings in distributing relevant information to the team.

Larger teams, of 9 or more people, are more likely to experience skills shortages, face communication issues, introduce code smells, and experience coordination challenges. Small teams of 2 – 3, engineers can easily communicate with each other to coordinate their activities. However, with every new team member, coordinating with everyone becomes more difficult and suboptimal solutions, especially code smells, find their way into the product.

3- Strategies to address technical debt

1.    As an engineer, be aware of good practices. Knowing the good practices can help to spot bad practices. Knowing the difference can help to better argue for or against certain solutions and be aware of potential negative side effects.

2.    On a team level, run retrospectives and learn how to remove friction from collaboration. With increasing team size, new practices supporting collaboration may be needed. For example, simple practices like daily standups, pair-programming, and a task board can make a significant difference in distributing knowledge and improving teamwork. Note that difficulties in communication and coordination are associated with a size of the whole team, not only the engineering part. Thus, everyone in a start-up team must participate in coordination and communication activities.

3.    On an organizational level, anticipate when to leverage on technical debt to speed up certain goals, and when to slow down and refactor. Our results show that most issues are experienced when a start-up attempts to on-board a large number of users and launch customizations for new markets.

Read more in the original paper: 

E. Klotins, M. Unterkalmsteiner, T. Gorschek et al., “Exploration of Technical Debt in Start-ups,” in International Conference of Software Engineering, 2018.

You may also like: 

  1. B. Stopford, K. Wallace and J. Allspaw, "Technical Debt: Challenges and Perspectives," in IEEE Software, vol. 34, no. 4, pp. 79-81, 2017.
  2. E. Wolff and S. Johann, "Technical Debt," in IEEE Software, vol. 32, no. 4, pp. 94-c3, July-Aug. 2015.
  3. C. Giardino, N. Paternoster, M. Unterkalmsteiner, T. Gorschek and P. Abrahamsson, "Software Development in Startup Companies: The Greenfield Startup Model," in IEEE Transactions on Software Engineering, vol. 42, no. 6, pp. 585-604, June 1 2016.

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