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Because software engineering often times distributes work across multiple people, a fundamental challenge in software engineering is ensuring that everyone on a team has the same understanding of what is being built and why. In the seminal book “The Mythical Man Month”, Fred Brooks argued that good software needs to have conceptual integrity, both in how it is designed, but also how it is implemented (Brooks 1995). This is the idea that whatever vision of what is being built must stay intact, even as the building of it gets distributed to multiple people. When multiple people are responsible for implementing a single coherent idea, how can they ensure they all build the same idea?
The solution is effective communication. As some events in industry have shown, communication requires empathy and teamwork. When communication is poor, teams become disconnected and produce software defects (Bettenburg & Hassan 2013). Therefore, achieving effective communication practices is paramount.
It turns out, however, that communication plays such a powerful role in software projects that it even shapes how projects unfold. Perhaps the most notable theory about the effect of communication is Conway's Law (Conway 1968). This theory argues that any designed system—software included—will reflect the communication structures involved in producing it. For example, think back to any course project where you divided the work into chunks and tried to combine them together into a final report at the end. The report and it's structure probably mirrored the fact that several distinct people worked on each section of the report, rather than sounding like a single coherent voice. The same things happen in software: if the team writing error messages for a website isn't talking to the team presenting them, you're probably going to get a lot of error messages that aren't so clear, may not fit on screen, and may not be phrased using the terminology of the rest of the site. On the other hand, if those two teams meet regularly to design the error mesages together, communicating their shared knowledge, they might produce a seamless, coherent experience. Not only does software follow this law when a project is created, they also follow this law as projects evolve over time (Zhou & Mockus 2011).
Because communication is so central, software engineers are constantly seeking information to further their work, going to their coworkers' desks, emailing them, chatting via messaging platforms, and even using social media (Ko et al. 2007). Some of the information that developers are seeking is easier to find than others. For example, in the study I just cited, it was pretty trivial to find information about how wrote a line of code or whether a build was done, but when the information they needed resided in someone else's head (e.g., why a particular line of code was written), it was slow or often impossible to retrieve it. Sometimes it's not even possible to find out who has the information. Researchers have investigated tools for trying to quantify expertise by automatically analyzing the code that developers have written, building platforms to help developers search for other developers who might know what they need to know (Mockus & Herbsleb 2002, Begel et al. 2010).
Communication is not always effective. In fact, there are many kinds of communication that are highly problematic in software engineering teams. For example, Perlow (1999) conducted an ethnography of one team and found a highly dysfunctional use of interruptions in which the most expert members of a team were constantly interrupted to “fight fires” (immediately address critical problems) in other parts of the organization, and then the organization rewarded them for their heroics. This not only made the most expert engineers less productive, but it also disincentivized the rest of the organization to find effective ways of preventing the disasters from occurring in the first place. Not all interruptions are bad, and they can increase productivity, but they do increase stress (Mark et al. 2008).
Communication isn't just about transmitting information; it's also about relationships and identity. For example, the dominant culture of many software engineering work environments—and even the perceived culture—is one that can deter many people from even pursuing careers in computer science. Modern work environments are still dominated by men, who speak loudly, out of turn, and disrespectfully, with some even bordering on sexual harassment. Similarly, software developers often have to work with people in other domains such as artists, content developers, data scientists, design researchers, designers, electrical engineers, mechanical engineers, product planners, program managers, and service engineers. One study found that developers' cross-disciplinary collaborations with people in these other domains required open-mindedness about the input of others, proactively informing everyone about code-related constraints, and ultimately seeing the broader picture of how pieces from different disciplines fit together; when developers didn't do these things, collaborations failed, and therefore projects failed (Li et al. 2017). These are not the conditions for trusting, effective communication.
When communication is effective, it still takes time. One of the key strategies for reducing the amount of communication necessary is knowledge sharing tools, which broadly refers to any information system that stores facts that developers would normally have to retrieve from a person. By storing them in a database and making them easy to search, teams can avoid interruptions. The most common knowledge sharing tools in software teams are issue trackers, which are often at the center of communication not only between developers, but also with every other part of a software organization (Bertram et al. 2010). Community portals, such as GitHub pages or Slack teams, can also be effective ways of sharing documents and archiving decisions (Treude & Storey 2011). Perhaps the most popular knowledge sharing tool in software engineering today is Stack Overflow, which archives facts about programming language and API usage. Such sites, while they can be great resources, have the same problems as many media, such as gender bias that prevent contributions from women from being rewarded as highly as contributions from men (May et al. 2019).
Because all of this knowledge is so critical to progress, when developers leave an organization and haven't archived their knowledge somewhere, it can be quite disruptive to progress. Organizations often have single points of failure, in which a single developer may be critical to a team's ability to maintain and enhance a software product (Rigby et al. 2016). When newcomers join a team and lack the right knowledge, they introduce defects (Foucault et al. 2015). Some companies try to mitigate this by rotating developers between projects, “cross-training” them to ensure that the necessary knowledge to maintain a project is distributed across multiple engineers.
What does all of this mean for you as an individual developer? To put it simply, don't underestimate the importance of talking. Know who you need to talk to, talk to them frequently, and to the extent that you can, write down what you know both to lessen the demand for talking and mitigate the risk of you not being available, but also to make your knowledge more precise and accessible in the future. It often takes decades for engineers to excel at communication. The very fact that you know why communication is important gives you an critical head start.
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