Constructing and analysing knowledge maps via source code repository analysis

Abstract

The most valuable asset held by software engineering organisations is arguably the knowledge held by its their employees. It is the creation, transfer and application of such organisational knowledge that provides such companies with the competitive edge required to provide value to their customers. With high staff turnover in the ICT industry, companies need to find a way to protect knowledge assets; or rather, they need to mitigate and address knowledge risk. Knowledge risk is defined as ”operational risk caused by a dependency on, loss of, unsuccessful intended or unintended transfer of knowledge assets, and results in a lack of, or non-exclusivity of these assets ”. One example of knowledge risk may be in scenarios when members of staff have a disproportionate amount of knowledge about knowledge assets when compared to their colleagues. This is an issue because in the event of such people leaving the company, access to their knowledge will be lost. In this project, we aimed to make the tacit notion of knowledge risk more explicit by analysing source code repositories and subsequently building knowledge maps for an organisation or project. The underlying hypothesis is that we can deduce ”what” and ”how much” a person knows about a particular knowledge asset based on the frequency and nature of their commits of code related to that asset. Following a literature review, we investigated this hypothesis by creating a tool that pulls information from source code repositories (e.g. Git), builds a mathematical representation of an organisation’s knowledge using graphs, and then applies graph theory to identify potential instances of knowledge risk. An evaluation exercise was executed with the help of open source repositories to determine the extent to which the constructed knowledge map represents the real situation.