Productivity is an important aspect of any software development project as it has direct implications on both the cost of software and the time taken to produce it. Though software development as a field has evolved significantly during the last few decades in terms of development processes, best practices and the emphasis thereon, the way in which the productivity of software developers is measured has remained comparatively stagnant. Some established metrics focus on a sole activity, such as programming, which paints an incomplete picture of productivity given the multitude of different activities that a software project consists of. Others are more process-oriented — purporting to measure all types of development activities — but require the use of estimation, a technique that is both time-consuming and prone to inaccuracy. A metric that is comprehensive, accurate and suitable in today's development landscape is needed.
In this thesis, we examine productivity measurement in software engineering from both theoretical and pragmatic perspectives in order to determine if a proposed metric, implicitly estimated velocity, could be a viable alternative for productivity measurement in Agile and Lean software teams. First, the theory behind measurement — terminology, data types and levels of measurement — is presented. The definition of the term productivity is then examined from a software engineering perspective. Based on this definition and the IEEE standard for validating software quality metrics, a set of criteria for validating productivity metrics is proposed. The motivations for measuring productivity and the factors that may impact it are then discussed and the benefits and drawbacks of established metrics — chief amongst which is productivity based on lines of code written — explored.
To assess the accuracy and overall viability of implicitly estimated velocity, a case study comparing the metric to LoC-based productivity measurement was carried out at the University of Helsinki's Software Factory. Two development projects were studied, both adopting Agile and Lean methodologies. Following a linear-analytical approach, quantitative data from both project artefacts and developer surveys indicated that implicitly estimated velocity is a metric more valid than LoC-based measurement in situations where the overall productivity of an individual or team is of more importance than programming productivity. In addition, implicitly estimated velocity was found to be more consistent and predictable than LoC-based measurement in most configurations, lending credence to the theory that implicitly estimated velocity can indeed replace LoC-based measurement in Agile and Lean software development environments.
