An empirical study of process-related attributes in segmented software cost-estimation relationships

Parametric software effort estimation models consisting on a single mathematical relationship suffer from poor adjustment and predictive characteristics in cases in which the historical database considered contains data coming from projects of a heterogeneous nature. The segmentation of the input domain according to clusters obtained from the database of historical projects serves as a tool for more realistic models that use several local estimation relationships. Nonetheless, it may be hypothesized that using clustering algorithms without previous consideration of the influence of well-known project attributes misses the opportunity to obtain more realistic segments. In this paper, we describe the results of an empirical study using the ISBSG-8 database and the EM clustering algorithm that studies the influence of the consideration of two process-related attributes as drivers of the clustering process: the use of engineering methodologies and the use of CASE tools. The results provide evidence that such consideration conditions significantly the final model obtained, even though the resulting predictive quality is of a similar magnitude.

Integrative workflow-embedded support for process automation and management

This paper presents the on-going research performed in order to integrate process automation and process management support in the context of media production. This has been addressed on the basis of a holistic approach to software engineering applied to media production modelling to ensure design correctness, completeness and effectiveness. The focus of the research and development has been to enhance the metadata management throughout the process in a similar fashion to that achieved in Decision Support Systems (DSS) to facilitate well-grounded business decisions. The paper sets out the aims and objectives and the methodology deployed. The paper describes the solution in some detail and sets out some preliminary conclusions and the planned future work.

Predicting fault inflow in iterative software development processes: an industrial evaluation

This paper addresses the need for accurate predictions on the fault inflow, i.e. the number of faults found in the consecutive project weeks, in highly iterative processes. In such processes, in contrast to waterfall-like processes, fault repair and development of new features run almost in parallel. Given accurate predictions on fault inflow, managers could dynamically re-allocate resources between these different tasks in a more adequate way. Furthermore, managers could react with process improvements when the expected fault inflow is higher than desired. This study suggests software reliability growth models (SRGMs) for predicting fault inflow. Originally developed for traditional processes, the performance of these models in highly iterative processes is investigated. Additionally, a simple linear model is developed and compared to the SRGMs. The paper provides results from applying these models on fault data from three different industrial projects. One of the key findings of this study is that some SRGMs are applicable for predicting fault inflow in highly iterative processes. Moreover, the results show that the simple linear model represents a valid alternative to the SRGMs, as it provides reasonably accurate predictions and performs better in many cases.

SPICE: a business process diagnostic tool for construction projects

The construction sector is under growing pressure to increase productivity and improve quality, most notably in reports by Latham (1994, Constructing the Team, HMSO, London) and Egan (1998, Rethinking Construction, HMSO, London). A major problem for construction companies is the lack of project predictability. One method of increasing predictability and delivering increased customer value is through the systematic management of construction processes. However, the industry has no methodological mechanism to assess process capability and prioritise process improvements. Standardized Process Improvement for Construction Enterprises (SPICE) is a research project that is attempting to develop a stepwise process improvement framework for the construction industry, utilizing experience from the software industry, and in particular the Capability Maturity Model (CMM), which has resulted in significant productivity improvements in the software industry. This paper introduces SPICE concepts and presents the results from two case studies conducted on design and build projects. These studies have provided further in-sight into the relevance and accuracy of the framework, as well as its value for the construction sector.

Generic unified modelling process for developing semantically rich, dynamic and temporal models

Models play a vital role in supporting a range of activities in numerous domains. We rely on models to support the design, visualisation, analysis and representation of parts of the world around us, and as such significant research effort has been invested into numerous areas of modelling; including support for model semantics, dynamic states and behaviour, temporal data storage and visualisation. Whilst these efforts have increased our capabilities and allowed us to create increasingly powerful software-based models, the process of developing models, supporting tools and /or data structures remains difficult, expensive and error-prone. In this paper we define from literature the key factors in assessing a model’s quality and usefulness: semantic richness, support for dynamic states and object behaviour, temporal data storage and visualisation. We also identify a number of shortcomings in both existing modelling standards and model development processes and propose a unified generic process to guide users through the development of semantically rich, dynamic and temporal models.

Methodology To model the energy and greenhouse gas emissions of electronic software distributions

A new electronic software distribution (ESD) life cycle analysis (LCA)methodology and model structure were constructed to calculate energy consumption and greenhouse gas (GHG) emissions. In order to counteract the use of high level, top-down modeling efforts, and to increase result accuracy, a focus upon device details and data routes was taken. In order to compare ESD to a relevant physical distribution alternative,physical model boundaries and variables were described. The methodology was compiled from the analysis and operational data of a major online store which provides ESD and physical distribution options. The ESD method included the calculation of power consumption of data center server and networking devices. An in-depth method to calculate server efficiency and utilization was also included to account for virtualization and server efficiency features. Internet transfer power consumption was analyzed taking into account the number of data hops and networking devices used. The power consumed by online browsing and downloading was also factored into the model. The embedded CO2e of server and networking devices was proportioned to each ESD process. Three U.K.-based ESD scenarios were analyzed using the model which revealed potential CO2e savings of 83% when ESD was used over physical distribution. Results also highlighted the importance of server efficiency and utilization methods.

Introducing "ecoputation": a universal systems design process

A universal systems design process is specified, tested in a case study and evaluated. It links English narratives to numbers using a categorical language framework with mathematical mappings taking the place of conjunctions and numbers. The framework is a ring of English narrative words between 1 (option) and 360 (capital); beyond 360 the ring cycles again to 1. English narratives are shown to correspond to the field of fractional numbers. The process can enable the development, presentation and communication of complex narrative policy information among communities of any scale, on a software implementation known as the "ecoputer". The information is more accessible and comprehensive than that in conventional decision support, because: (1) it is expressed in narrative language; and (2) the narratives are expressed as compounds of words within the framework. Hence option generation is made more effective than in conventional decision support processes including Multiple Criteria Decision Analysis, Life Cycle Assessment and Cost-Benefit Analysis.The case study is of a participatory workshop in UK bioenergy project objectives and criteria, at which attributes were elicited in environmental, economic and social systems. From the attributes, the framework was used to derive consequences at a range of levels of precision; these are compared with the project objectives and criteria as set out in the Case for Support. The design process is to be supported by a social information manipulation, storage and retrieval system for numeric and verbal narratives attached to the "ecoputer". The "ecoputer" will have an integrated verbal and numeric operating system. Novel design source code language will assist the development of narrative policy. The utility of the program, including in the transition to sustainable development and in applications at both community micro-scale and policy macro-scale, is discussed from public, stakeholder, corporate, Governmental and regulatory perspectives.