SERL - Software Engineering Research Laboratory
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The Software Engineering Research Lab (SERL) at AUT University undertakes world-class research directed at understanding and improving the practice of software professionals in their creation and preservation of software systems. We are interested in all models of software provision – bespoke development, package and component customisation, free/libre open source software (FLOSS) development, and delivery of software as a service (SaaS). The research we carry out may relate to just one or all of these models.
- ItemProgress Report on a Proposed Theory for Software Development(SciTePress, 2015-08)There is growing acknowledgement within the software engineering community that a theory of software development is needed to integrate the myriad methodologies that are currently popular, some of which are based on opposing perspectives. We have been developing such a theory for a number of years. In this position paper, we overview our theory along with progress made thus far. We suggest that, once fully developed, this theory, or one similar to it, may be applied to support situated software development, by providing an overarching model within which software initiatives might be categorised and understood. Such understanding would inevitably lead to greater predictability with respect to outcomes.
- ItemPackaged Software Implementation Requirements Engineering by Small Software Enterprises(IEEE Computer Society, 2013) Jebreen, I; Wellington, R; MacDonell, SGSmall to medium sized business enterprises (SMEs) generally thrive because they have successfully done something unique within a niche market. For this reason, SMEs may seek to protect their competitive advantage by avoiding any standardization encouraged by the use of packaged software (PS). Packaged software implementation at SMEs therefore presents challenges relating to how best to respond to mismatches between the functionality offered by the packaged software and each SME's business needs. An important question relates to which processes small software enterprises - or Small to Medium-Sized Software Development Companies (SMSSDCs) - apply in order to identify and then deal with these mismatches. To explore the processes of packaged software (PS) implementation, an ethnographic study was conducted to gain in-depth insights into the roles played by analysts in two SMSSDCs. The purpose of the study was to understand PS implementation in terms of requirements engineering (or 'PSIRE'). Data collected during the ethnographic study were analyzed using an inductive approach. Based on our analysis of the cases we constructed a theoretical model explaining the requirements engineering process for PS implementation, and named it the PSIRE Parallel Star Model. The Parallel Star Model shows that during PSIRE, more than one RE process can be carried out at the same time. The Parallel Star Model has few constraints, because not only can processes be carried out in parallel, but they do not always have to be followed in a particular order. This paper therefore offers a novel investigation and explanation of RE practices for packaged software implementation, approaching the phenomenon from the viewpoint of the analysts, and offers the first extensive study of packaged software implementation RE (PSIRE) in SMSSDCs.
- ItemA Taxonomy of Data Quality Challenges in Empirical Software Engineering(IEEE, 2013)Reliable empirical models such as those used in software effort estimation or defect prediction are inherently dependent on the data from which they are built. As demands for process and product improvement continue to grow, the quality of the data used in measurement and prediction systems warrants increasingly close scrutiny. In this paper we propose a taxonomy of data quality challenges in empirical software engineering, based on an extensive review of prior research. We consider current assessment techniques for each quality issue and proposed mechanisms to address these issues, where available. Our taxonomy classifies data quality issues into three broad areas: first, characteristics of data that mean they are not fit for modeling, second, data set characteristics that lead to concerns about the suitability of applying a given model to another data set, and third, factors that prevent or limit data accessibility and trust. We identify this latter area as of particular need in terms of further research. © 2013 IEEE.
- ItemOnshore to near-shore outsourcing transitions: unpacking tensions(IEEE, 2015-07-13) Clear, AG; Raza, B; Clear, T; MacDonell, SGThis study is directed towards highlighting tensions of incoming and outgoing vendors during outsourcing in a near-shore context. Incoming-and-outgoing of vendors generate a complex form of relationship in which the participating organizations cooperate and compete simultaneously. It is of great importance to develop knowledge about this kind of relationship typically in the current GSE-related multi-sourcing environment. We carried out a longitudinal case study and utilized data from the 'Novo pay' project, which is available in the public domain. This project involved an outgoing New Zealand based vendor and incoming Australian based vendor. The results show that the demand for the same human resources, dependency upon cooperation and collaboration between vendors, reliance on each other system's configurations and utilizing similar strategies by the client, which worked for the previous vendor, generated a set of tensions which needed to be continuously managed throughout the project.
- ItemAn empirical cognitive model of the development of shared understanding of requirements(Springer, 2014-06-01) Buchan, JIt is well documented that customers and software development teams need to share and refine understanding of the requirements throughout the software development lifecycle. The development of this shared understand- ing is complex and error-prone however. Techniques and tools to support the development of a shared understanding of requirements (SUR) should be based on a clear conceptualization of the phenomenon, with a basis on relevant theory and analysis of observed practice. This study contributes to this with a detailed conceptualization of SUR development as sequence of group-level state transi- tions based on specializing the Team Mental Model construct. Furthermore it proposes a novel group-level cognitive model as the main result of an analysis of data collected from the observation of an Agile software development team over a period of several months. The initial high-level application of the model shows it has promise for providing new insights into supporting SUR development.