Finding relationships between effort and other variables in the SEL

Estimating the amount of effort required for a software development project is one of the major aspects of resource estimation for that project. In this study, the relationship between effort and other variables for 23 Software Engineering Laboratory (SEL) projects that were developed for NASA/Goddard Space Flight Center was examined. These variables fell into two categories: those which can be determined in the early stages of project development and may therefore be useful in a baseline equation for predicting effort in future projects, and those which can be used mainly to characterize or evaluate effort requirements and thus enhance the understanding of the software development process in this environment. Some results of the analyses are presented

What's taking so long? A collaborative method of collecting designers' insight into what factors increase design effort levels in projects

Design effort is a key resource for product design projects. Environments where design effort is scarce, and therefore valuable, include hackathons and other time-limited design challenges. Predicting design effort needs is key to successful project planning; therefore, understanding design effort-influencing factors (objective considerations that are universally accepted to exert influence on a subject, that is, types of phenomena, constraints, characteristics, or stimulus) will aid in planning success, offering an improved organizational understanding of product design, characterizing the design space and providing a perspective to assess project briefs from the outset. This paper presents the Collaborative Factor Identification for Design Effort (CoFIDE) Method based on Hird's (2012) method for developing resource forecasting tools for new product development teams. CoFIDE enables the collection of novel data of, and insight into, the collaborative understanding and perceptions of the most influential factors of design effort levels in design projects and how their behavior changes over the course of design projects. CoFIDE also enables design teams, hackathon teams, and makerspace collaborators to characterize their creative spaces, to quickly enable mutual understanding, without the need for complex software and large bodies of past project data. This insight offers design teams, hackathon teams, and makerspace collaborators opportunities to capitalize on positive influences while minimizing negative influences. This paper demonstrates the use of CoFIDE through a case study with a UK-based product design agency, which enabled the design team to identify and model the behavior of four influential factors

Evaluating prediction systems in software project estimation

This is the Pre-print version of the Article - Copyright @ 2012 ElsevierContext: Software engineering has a problem in that when we empirically evaluate competing prediction systems we obtain conflicting results. Objective: To reduce the inconsistency amongst validation study results and provide a more formal foundation to interpret results with a particular focus on continuous prediction systems. Method: A new framework is proposed for evaluating competing prediction systems based upon (1) an unbiased statistic, Standardised Accuracy, (2) testing the result likelihood relative to the baseline technique of random ‘predictions’, that is guessing, and (3) calculation of effect sizes. Results: Previously published empirical evaluations of prediction systems are re-examined and the original conclusions shown to be unsafe. Additionally, even the strongest results are shown to have no more than a medium effect size relative to random guessing. Conclusions: Biased accuracy statistics such as MMRE are deprecated. By contrast this new empirical validation framework leads to meaningful results. Such steps will assist in performing future meta-analyses and in providing more robust and usable recommendations to practitioners.Martin Shepperd was supported by the UK Engineering and Physical Sciences Research Council (EPSRC) under Grant EP/H050329