Juan Jose Cuadrado-Gallego

Detecting Fault Modules Applying Feature Selection to Classifiers

At present, automated data collection tools allow us to collect large amounts of information, not without associated problems. This paper, we apply feature selection to several software engineering databases selecting attributes with the final aim that project managers can have a better global vision of the data they manage. In this paper, we make use of attribute selection techniques in different datasets publicly available (PROMISE repository), and different data mining algorithms for classification to defect faulty modules. The results show that in general, smaller datasets with less attributes maintain or improve the prediction capability with less attributes than the original datasets.

Software Process and Product Measurement

This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Software Measurement, IWSM-Mensura 2007, held in Palma de Mallorca, Spain, in November 2007. The 16 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers deal with aspects of software measurement like function-points measurement, effort and cost estimates, prediction, industrial experiences in software measurement, planning and implementing measurement, measurement-based software process improvement, best practices in software measurement, usability and user interaction measurement, measurement of open source projects, teaching and learning software measurement as well as new trends and ontologies for software measurement.

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.

An experimental study on the conversion between IFPUG and COSMIC functional size measurement units

The adoption of functional size measurement (FSM) methods in software organizations is growing. In particular, special attention is being paid to the COSMIC method, because of its novelties against 1st generation FSM methods such as IFPUG FPA. One of the main problems facing organizations wanting to use COSMIC is how to properly convert the software functional size of the projects in their portfolio measured by the previously adopted FSM method to the size measured by the new method. The objective of this paper is to find a sound mathematical basis for converting an IFPUG measurement to a COSMIC measurement. In the light of previously published researches, parallel measurements were performed to establish three new datasets (respectively composed by 21, 14 and 35 data points) and verified by an expert measurer, certified on both techniques. In order to obtain a more precise solution, the search for a mathematical relationship has been run using new nonlinear equation types. Results from the analysis confirmed an approximated conversion factor of 1:1, within a range between 0.9 and 1.1, but moving from a larger number of data points analyzed then in past studies. These results can be very useful for those companies starting to use their benchmarking databases populated in IFPUG FP units to projects measured in COSMIC FP.

e-Learning in Project Management Using Simulation Models: A Case Study Based on the Replication of an Experiment

Current e-learning systems are increasing their importance in higher education. However, the state of the art of e-learning applications, besides the state of the practice, does not achieve the level of interactivity that current learning theories advocate. In this paper, the possibility of enhancing e-learning systems to achieve deep learning has been studied by replicating an experiment in which students had to learn basic software engineering principles. One group learned these principles using a static approach, while the other group learned the same principles using a system-dynamics-based approach, which provided interactivity and feedback. The results show that, quantitatively, the latter group achieved a better understanding of the principles; furthermore, qualitatively, they enjoyed the learning experience

A standards-based reference framework for system portability requirements

In the system requirements phase, the non-functional requirements (NFR) are often captured only generically at a fairly high level, and they do not yet include the levels of detail necessary for the system engineers to allocate them as specific functionalities to be handled either by the software or the hardware, or a specific combination of the two. The European ECSS series of standards for the aerospace industry includes portability requirements as one of sixteen types of non functional requirements (NFR) for embedded and real-time software. A number of portability-related concepts are dispersed throughout the ECSS, IEEE-830, ISO 9126, ISO 24765, and ISO 2382-1 standards to describe, at varying levels of detail, the various types of candidate portability requirements at the system, software, and hardware levels. This paper organizes these dispersed portability concepts and terms into a standards-based reference framework of system portability requirements. The availability of this framework can facilitate the early identification and specification of the system portability NFR and their detailed allocation as specific portability functions to be handled by the specified allocation to hardware or software, or a specific combination of the two. The approach selected in this research for the structure of this reference framework is based on the generic model of software proposed in the COSMIC-ISO 19761 model, thereby allowing the functional size of the portability requirements allocated to software to be measured.

Convertibility between IFPUG and COSMIC functional size measurements

Since 1984 the International Function Point Users Group (IFPUG) has produced and maintained a set of standards and technical documents about a functional size measurement methods, known as IFPUG, based on Albrecht Fuction Points. On the other hand, in 1998, the Common Software Measurement International Consortium (COSMIC) proposed an improved measurement method known as Full Function Points (FFP). Both the IFPUG and the COSMIC methods both measure functional size of software, but produce different results. In this paper, we propose a model to convert functional size measures obtained with the IFPUG method to the corresponding COSMIC measures. We also present the validation of the model using 33 software projects measured with both methods. This approach may be beneficial to companies using both methods or migrating to COSMIC such that past data in IFPUG can be considered for future estimates using COSMIC and as a validation procedure.

On the conversion between IFPUG and COSMIC software functional size units: A theoretical and empirical study

Since 1984 the International Function Point Users Group (IFPUG) has produced and maintained a set of standards and technical documents about a functional size measurement methods, known as IFPUG, based on Albrecht function points. On the other hand, in 1998, the Common Software Measurement International Consortium (COSMIC) proposed an improved measurement method known as full function points (FFP). Both the IFPUG and the COSMIC methods both measure functional size of software, but produce different results. In this paper, we propose a model to convert functional size measures obtained with the IFPUG method to the corresponding COSMIC measures. We also present the validation of the model using 33 software projects measured with both methods. This approach may be beneficial to companies using both methods or migrating to COSMIC such that past data in IFPUG can be considered for future estimates using COSMIC and as a validation procedure.

Attribute Selection in Software Engineering Datasets for Detecting Fault Modules

Decision making has been traditionally based on managers experience. At present, there is a number of software engineering (SE) repositories, and furthermore, automated data collection tools allow managers to collect large amounts of information, not without associated problems. On the one hand, such a large amount of information can overload project managers. On the other hand, problems found in generic project databases, where the data is collected from different organizations, is the large disparity of its instances. In this paper, we characterize several software engineering databases selecting attributes with the final aim that project managers can have a better global vision of the data they manage. In this paper, we make use of different data mining algorithms to select attributes from the different datasets publicly available (PROMISE repository), and then, use different classifiers to defect faulty modules. The results show that in general, the smaller datasets maintain the prediction capability with a lower number of attributes than the original datasets.

IFPUG-COSMIC Statistical Conversion

One of the main issues faced within the Functional Size Measurement (FSM) community is the convertibility issue between FSM methods. A particular attention during last years was devoted to find a mathematical function for converting IFPUG functional size units to the newer COSMIC ones. Moving from the data sets and experiences described in previous studies, some attention points about cost and quality from the data gathering process emerge. This paper analyzes the data gathering process issue and proposes a solution for overcoming such difficulties. From an application of a repeteable and verifiable procedure, performed in a university course on Software Engineering with the support of an experienced measurer, two new data sets were derived. Finally an analysis of all datasets was done, presenting a possible interval for the conversion between IFPUG-COSMIC fsu.