Definition of an eXecutable SPEM 2.0

International audienceOne major advantage of executable models is that once constructed, they can be run, checked, validated and improved in short incremental and iterative cycles. In the field of Software Process Modeling, process models have not yet reached the level of precision that would allow their execution. Recently the OMG issued a new revision of its standard for Software Process Modeling, namely SPEM2.0. However, even if executability was defined as a mandatory requirement in the RFP (Request For Proposal), the adopted specification does not fulfill it. This paper presents a critical analysis on the newly defined standard and addresses its lacks in terms of executability. An approach is proposed in order to extend the standard with a set of concepts and behavioural semantics that would allow SPEM2.0 process models to be checked through a mapping to Petri nets and monitored through a transformation into BPEL

Software Outsourcing Subcontracting and its Impacts: An Empirical Investigation

China now is one of the most important places where software outsourcing businesses are flourishing. However, the subcontracting in the current software outsourcing practices has not received enough attentions. This research attempts to further the understanding on this issue. Mixed empirical research approaches were used to explore the extent and the impacts of the outsourcing subcontracting. The findings suggest the subcontracting widely exists in current China outsourcing industry. Its major enabling factors were also identified. While subcontracting provides the industry with specialized services as well as organizational and managerial flexibility in a low cost way, it also introduces some negative influences. Four future trends are also addressed in this paper

Predicting software project effort: A grey relational analysis based method

This is the post-print version of the final paper published in Expert Systems with Applications. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2011 Elsevier B.V.The inherent uncertainty of the software development process presents particular challenges for software effort prediction. We need to systematically address missing data values, outlier detection, feature subset selection and the continuous evolution of predictions as the project unfolds, and all of this in the context of data-starvation and noisy data. However, in this paper, we particularly focus on outlier detection, feature subset selection, and effort prediction at an early stage of a project. We propose a novel approach of using grey relational analysis (GRA) from grey system theory (GST), which is a recently developed system engineering theory based on the uncertainty of small samples. In this work we address some of the theoretical challenges in applying GRA to outlier detection, feature subset selection, and effort prediction, and then evaluate our approach on five publicly available industrial data sets using both stepwise regression and Analogy as benchmarks. The results are very encouraging in the sense of being comparable or better than other machine learning techniques and thus indicate that the method has considerable potential.National Natural Science Foundation of Chin

Grounding Functional Requirements Classification in Organizational Semiotics

An information system has its requirements rooted in organizational policies and behaviour, the complexity of which is governed by the hierarchy and the dependencies of the activities within the organization. This complexity makes requirements analysis for an envisioned information system an intricately challenging task. The absence of well‐defined body of knowledge clearly specifying which requirements must be looked for further deepens the challenge of requirements analysis. Though requirements are broadly classified as functional and non‐functional, a special concern is required for functional requirements as the information system is expected to meet the behaviour of the organization. We explore the role of organizational semiotics in extracting and analysing functional requirements for an envisioned information system. We also report the results of supervised learning to automatically extract the functional requirements from the existing available documentation