Using grounded theory to understand software process improvement: A study of Irish software product companies

Software Process Improvement (SPI) aims to understand the software process as it is used within an organisation and thus drive the implementation of changes to that process to achieve specific goals such as increasing development speed, achieving higher product quality or reducing costs. Accordingly, SPI researchers must be equipped with the methodologies and tools to enable them to look within organisations and understand the state of practice with respect to software process and process improvement initiatives, in addition to investigating the relevant literature. Having examined a number of potentially suitable research methodologies, we have chosen Grounded Theory as a suitable approach to determine what was happening in actual practice in relation to software process and SPI, using the indigenous Irish software product industry as a test-bed. The outcome of this study is a theory, grounded in the field data, that explains when and why SPI is undertaken by the software industry. The objective of this paper is to describe both the selection and usage of grounded theory in this study and evaluate its effectiveness as a research methodology for software process researchers. Accordingly, this paper will focus on the selection and usage of grounded theory, rather than results of the SPI study itself

A hierarchy of SPI activities for software SMEs: results from ISO/IEC 12207-based SPI assessments

In an assessment of software process improvement (SPI) in 15 software small- and –medium-sized enterprises (software SMEs), we applied the broad spectrum of software specific and system context processes in ISO/IEC 12207 to the task of examining SPI in practice. Using the data collected in the study, we developed a four-tiered pyramidal hierarchy of SPI for software SMEs, with processes in the higher tiers undergoing SPI in more companies than processes on lower level tiers. The development of the hierarchy of SPI activities for software SMEs can facilitate future evolutions of process maturity reference frameworks, such as ISO/IEC 15504, in better supporting software development in software SMEs. Furthermore, the findings extend our body of knowledge concerning the practice of SPI in software SMEs, a large and vital sector of the software development community that has largely avoided the implementation of established process maturity and software quality management standards

Business Process Management Education in Academia: Status, challenges, and Recommendations

In response to the growing proliferation of Business Process Management (BPM) in industry and the demand this creates for BPM expertise, universities across the globe are at various stages of incorporating knowledge and skills in their teaching offerings. However, there are still only a handful of institutions that offer specialized education in BPM in a systematic and in-depth manner. This article is based on a global educators’ panel discussion held at the 2009 European Conference on Information Systems in Verona, Italy. The article presents the BPM programs of five universities from Australia, Europe, Africa, and North America, describing the BPM content covered, program and course structures, and challenges and lessons learned. The article also provides a comparative content analysis of BPM education programs illustrating a heterogeneous view of BPM. The examples presented demonstrate how different courses and programs can be developed to meet the educational goals of a university department, program, or school. This article contributes insights on how best to continuously sustain and reshape BPM education to ensure it remains dynamic, responsive, and sustainable in light of the evolving and ever-changing marketplace demands for BPM expertise

A quality management based on the Quality Model life cycle

Managing quality is a hard and expensive task that involves the execution and control of processes and techniques. For a good quality management, it is important to know the current state and the objective to be achieved. It is essential to take into account with a Quality Model that specifies the purposes of managing quality. QuEF (Quality Evaluation Framework) is a framework to manage quality in MDWE (Model-driven Web Engineering). This paper suggests managing quality but pointing out the Quality Model life cycle. The purpose is to converge toward a quality continuous improvement by means of reducing effort and time.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Ministerio de Ciencia e Innovación TIN 2010-12312-EJunta de Andalucía TIC-578

Exploring Application Performance on Emerging Hybrid-Memory Supercomputers

Next-generation supercomputers will feature more hierarchical and heterogeneous memory systems with different memory technologies working side-by-side. A critical question is whether at large scale existing HPC applications and emerging data-analytics workloads will have performance improvement or degradation on these systems. We propose a systematic and fair methodology to identify the trend of application performance on emerging hybrid-memory systems. We model the memory system of next-generation supercomputers as a combination of "fast" and "slow" memories. We then analyze performance and dynamic execution characteristics of a variety of workloads, from traditional scientific applications to emerging data analytics to compare traditional and hybrid-memory systems. Our results show that data analytics applications can clearly benefit from the new system design, especially at large scale. Moreover, hybrid-memory systems do not penalize traditional scientific applications, which may also show performance improvement.Comment: 18th International Conference on High Performance Computing and Communications, IEEE, 201

How can SMEs benefit from big data? Challenges and a path forward

Big data is big news, and large companies in all sectors are making significant advances in their customer relations, product selection and development and consequent profitability through using this valuable commodity. Small and medium enterprises (SMEs) have proved themselves to be slow adopters of the new technology of big data analytics and are in danger of being left behind. In Europe, SMEs are a vital part of the economy, and the challenges they encounter need to be addressed as a matter of urgency. This paper identifies barriers to SME uptake of big data analytics and recognises their complex challenge to all stakeholders, including national and international policy makers, IT, business management and data science communities. The paper proposes a big data maturity model for SMEs as a first step towards an SME roadmap to data analytics. It considers the ‘state-of-the-art’ of IT with respect to usability and usefulness for SMEs and discusses how SMEs can overcome the barriers preventing them from adopting existing solutions. The paper then considers management perspectives and the role of maturity models in enhancing and structuring the adoption of data analytics in an organisation. The history of total quality management is reviewed to inform the core aspects of implanting a new paradigm. The paper concludes with recommendations to help SMEs develop their big data capability and enable them to continue as the engines of European industrial and business success. Copyright © 2016 John Wiley & Sons, Ltd.Peer ReviewedPostprint (author's final draft