Empirical Studies of Evolving Systems

This paper describes the results of the working group investigating the issues of empirical studies for evolving systems. The groups found that there were many issues that were central to successful evolution and this concluded that this is a very important area within software engineering. Finally nine main areas were selected for consideration. For each of these areas the central issues were identified as well as success factors. In some cases success stories were also described and the critical factors accounting for the success analysed. In some cases it was later found that a number of areas were so tightly coupled that it was important to discuss them together

Making inferences with small numbers of training sets

A potential methodological problem with empirical studies that assess project effort prediction system is discussed. Frequently, a hold-out strategy is deployed so that the data set is split into a training and a validation set. Inferences are then made concerning the relative accuracy of the different prediction techniques under examination. This is typically done on very small numbers of sampled training sets. It is shown that such studies can lead to almost random results (particularly where relatively small effects are being studied). To illustrate this problem, two data sets are analysed using a configuration problem for case-based prediction and results generated from 100 training sets. This enables results to be produced with quantified confidence limits. From this it is concluded that in both cases using less than five training sets leads to untrustworthy results, and ideally more than 20 sets should be deployed. Unfortunately, this raises a question over a number of empirical validations of prediction techniques, and so it is suggested that further research is needed as a matter of urgency

A framework for the simulation of structural software evolution

This is the author's accepted manuscript. The final published article is available from the link below. Copyright @ 2008 ACM.As functionality is added to an aging piece of software, its original design and structure will tend to erode. This can lead to high coupling, low cohesion and other undesirable effects associated with spaghetti architectures. The underlying forces that cause such degradation have been the subject of much research. However, progress in this field is slow, as its complexity makes it difficult to isolate the causal flows leading to these effects. This is further complicated by the difficulty of generating enough empirical data, in sufficient quantity, and attributing such data to specific points in the causal chain. This article describes a framework for simulating the structural evolution of software. A complete simulation model is built by incrementally adding modules to the framework, each of which contributes an individual evolutionary effect. These effects are then combined to form a multifaceted simulation that evolves a fictitious code base in a manner approximating real-world behavior. We describe the underlying principles and structures of our framework from a theoretical and user perspective; a validation of a simple set of evolutionary parameters is then provided and three empirical software studies generated from open-source software (OSS) are used to support claims and generated results. The research illustrates how simulation can be used to investigate a complex and under-researched area of the development cycle. It also shows the value of incorporating certain human traits into a simulation—factors that, in real-world system development, can significantly influence evolutionary structures

Análisis de la variabilidad de la lluvia, la evapotranspiración e índices de vegetación en áreas agrícolas de Entre Ríos

Sobre la base de los resultados del proyecto anterior ‘Integración de datos agrometeorológicos, de sensores remotos y de cultivos mediante técnicas de geoinformación y modelos en el Centro-Oeste de Entre Ríos (PICT 06-1221 PIDUNER 2128) y tomando en consideración el efecto de las anomalías en la producción de granos en la provincia de Entre Ríos se hace evidente la necesidad e importancia de llevar adelante estudios que posibiliten una mayor comprensión de la variabilidad de la lluvia, la evapotranspiración e índices de vegetación y las relaciones con la producción. Esta reseña del proyecto se refiere a dos aspectos del mismo: meteorología agrícola y teledetección aplicada. La primera dirigida a mejorar la información agrometeorológica, a conocer la variabilidad espacial y temporal e investigar asociaciones o efectos en los cultivos. La segunda para: estudiar el comportamiento de la reflectividad de los cultivos de maíz, soja y trigo mediante índices, poner a prueba técnicas avanzadas de procesamiento y manejo de datos de satélites de recursos naturales (Landsat, Modis y nuevos satélites).El proyecto pertenece a un área científica con escaso desarrollo en nuestro país y casi nula en la provincia, pero la importancia actual y el carácter prioritario para los años venideros -por el potencial impacto- señalan la necesidad de iniciar y afianzar estas líneas de investigación y formar recursos humanos capaces de conducirlas

Scenario-Based Design Theorizing:The Case of a Digital Idea Screening Cockpit

As ever more companies encourage employees to innovate, a surplus of ideas has become reality in many organizations – often exceeding the available resources to execute them. Building on insights from a literature review and a 3-year collaboration with a banking software provider, the paper suggests a Digital Idea Screening Cockpit (DISC) to address this challenge. Following a design science research approach, it suggests a prescriptive design theory that provides practitioner-oriented guidance for implementing a DISC. The study shows that, in order to facilitate the assessment, selection, and tracking of ideas for different stakeholders, such a system needs to play a dual role: It needs to structure decision criteria and at the same be flexible to allow for creative expression. Moreover, the paper makes a case for scenario-based design theorizing by developing design knowledge via scenarios

A metrics suite for object oriented design

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