Barbara Russo

Identification of defect-prone classes in telecommunication software systems using design metrics

The goal of this paper is to investigate the relation between object-oriented design choices and defects in software systems, with focus on a real-time telecommunication domain. The design choices are measured using the widely accepted metrics suite proposed by Chidamber and Kemerer for object oriented languages [S.R. Chidamber, C.F. Kemerer, A metrics suite for object oriented design, IEEE Transactions on Software Engineering 20 (6) (1994) 476-493]. This paper reports the results of an extensive case study, which strongly reinforces earlier, mainly anecdotal, evidence that design aspects related to communication between classes can be used as indicators of the most defect-prone classes. Statistical models applicable for the non-normally distributed count data are used, such as Poisson regression, negative binomial regression, and zero-inflated negative binomial regression. The performances of the models are assessed using correlations, dispersion coefficients and Alberg diagrams. The zero-inflated negative binomial regression model based on response for a class shows the best overall ability to describe the variability of the number of defects in classes.

Managing uncertainty in requirements: a survey in documentation-driven and agile companies

This paper investigates commonalities and differences between agile and documentation-driven approaches in managing uncertainty in requirement gathering. The research method is a survey collected interviewing sixteen project managers of Italian software companies, 8 using agile methods, and 8 using documentation-driven methods. The results show that agile and document-driven companies consider in a different way the problem of changing requirements and the related uncertainty; thus, they manage differently requirements gathering and the relationship with the customer

An Empirical Exploration of the Distributions of the Chidamber and Kemerer Object-Oriented Metrics Suite

The object-oriented metrics suite proposed by Chidamber and Kemerer (CK) is a measurement approach towards improved object-oriented design and development practices. However, existing studies evidence traces of collinearity between some of the metrics and low ranges of other metrics, two facts which may endanger the validity of models based on the CK suite. As high correlation may be an indicator of collinearity, in this paper, we empirically determine to what extent high correlations and low ranges might be expected among CK metrics.To draw as much general conclusions as possible, we extract the CK metrics from a large data set (200 public domain projects) and we apply statistical meta-analysis techniques to strengthen the validity of our results. Homogenously through the projects, we found a moderate (∼0.50) to high correlation (>0.80) between some of the metrics and low ranges of other metrics.Results of this empirical analysis supply researchers and practitioners with three main advises: a) to avoid the use in prediction systems of CK metrics that have correlation more than 0.80 b) to test for collinearity those metrics that present moderate correlations (between 0.50 and 0.60) c) to avoid the use as response in continuous parametric regression analysis of the metrics presenting low variance. This might therefore suggest that a prediction system may not be based on the whole CK metrics suite, but only on a subset consisting of those metrics that do not present either high correlation or low ranges.

Release planning of mobile apps based on user reviews

Developers have to to constantly improve their apps by fixing critical bugs and implementing the most desired features in order to gain shares in the continuously increasing and competitive market of mobile apps. A precious source of information to plan such activities is represented by reviews left by users on the app store. However, in order to exploit such information developers need to manually analyze such reviews. This is something not doable if, as frequently happens, the app receives hundreds of reviews per day. In this paper we introduce CLAP (Crowd Listener for releAse Planning), a thorough solution to (i) categorize user reviews based on the information they carry out (e.g., bug reporting), (ii) cluster together related reviews (e.g., all reviews reporting the same bug), and (iii) automatically prioritize the clusters of reviews to be implemented when planning the subsequent app release. We evaluated all the steps behind CLAP, showing its high accuracy in categorizing and clustering reviews and the meaningfulness of the recommended prioritizations. Also, given the availability of CLAP as a working tool, we assessed its practical applicability in industrial environments.

Adoption of free/libre open source software in public organizations: factors of impact

Purpose – In this paper the authors aim to investigate the importance of factors for the adoption of free/libre open source software (FLOSS) in the public sector. They seek to evaluate how different factors impact during the initiation and implementation phases of the adoption process.Design/methodology/approach – The authors base the methodological approach on two exploratory case studies with a contrasting result logic. They build a multi‐level framework grounded both on literature review, and feedback from stakeholders. They then apply the framework to two case studies to better frame the findings. They consider phases of adoption (initiation, implementation) and the levels of adoption (technological, organizational, environmental, individual).Findings – In the case studies, the authors found the importance of a strong and decision‐centric management board to give the impulse for the initiation phase of the process. As perceived by the stakeholders, a strong governmental support is of paramount importa...

The use of empirical methods in Open Source Software research: Facts, trends and future directions

Open Source Software (OSS) is a field of study with increasing interest of researchers. By its nature, OSS is especially suitable for empirical research. A great number of OSS related empirical studies have been conducted, but no effort has been made to systematically review the published evidence. This paper presents the results of a systematic review to investigate research topics and used methods in OSS related research. We present our results as facts and trends in this field and provide directions for future research.

Knowledge transfer in system modeling and its realization through an optimal allocation of information granularity

In this study, we introduce and discuss a concept of knowledge transfer in system modeling. In a nutshell, knowledge transfer is about forming ways on how a source of knowledge (namely, an existing model) can be used in presence of new, very limited experimental evidence. In virtue of the nature of the problem at hand (a situation encountered quite commonly, e.g. in project cost estimation), new data could be very limited and this scarcity of data makes it insufficient to construct a new model. At the same time, the new data originate from a similar (but not the same) phenomenon (process) for which the original model has been constructed so the existing model, even though it could applied, has to be treated with a certain level of reservation. Such situations can be encountered, e.g. in software engineering where in spite existing similarities, each project, process, or product exhibits its own unique characteristics. Taking this into consideration, the existing model is generalized (abstracted) by forming its granular counterpart - granular model where its parameters are regarded as information granules rather than numeric entities, viz. their non-numeric (granular) version is formed based on the values of the numeric parameters present in the original model. The results produced by the granular model are also granular and in this manner they become reflective of the differences existing between the current phenomenon and the process for which the previous model has been formed. In the study on knowledge transfer and reusability, information granularity is viewed as an important design asset and as such it is subject to optimization. We formulate an optimal information granularity allocation problem: assuming a certain level of granularity, distribute it optimally among the parameters of the model (making them granular) so that a certain data coverage criterion is maximized. While the underlying concept is general and applicable to a variety of models, in this study, we discuss its use to fuzzy neural networks with intent to clearly visualize the advantages of the approach and emphasize various ways of forming granular versions of the weights (parameters) of the connections of the network. Several granularity allocation protocols (ranging from a uniform distribution of granularity, symmetric and asymmetric schemes of allocation) are discussed and the effectiveness of each of them is quantified. The use of Particle Swarm Optimization (PSO) as the underlying optimization tool to realize optimal granularity allocation is discussed.

Too long; didn't watch!: extracting relevant fragments from software development video tutorials

When knowledgeable colleagues are not available, developers resort to offline and online resources, e.g., tutorials, mailing lists, and Q&A websites. These, however, need to be found, read, and understood, which takes its toll in terms of time and mental energy. A more immediate and accessible resource are video tutorials found on the web, which in recent years have seen a steep increase in popularity. Nonetheless, videos are an intrinsically noisy data source, and finding the right piece of information might be even more cumbersome than using the previously mentioned resources. We present CodeTube, an approach which mines video tutorials found on the web, and enables developers to query their contents. The video tutorials are split into coherent fragments, to return only fragments related to the query. These are complemented with information from additional sources, such as Stack Overflow discussions. The results of two studies to assess CodeTube indicate that video tutorials—if appropriately processed—represent a useful, yet still under-utilized source of information for software development.

Agile Technologies in Open Source Development

The analysis of commonalities and differences between agile technology and open source software development is needed to understand how advancement approaches have evolved and whether they produce concrete benefits in terms of software quality and customer satisfaction. Agile Technologies in Open Source Development explores the overlap between open source and agile technologies, providing valuable strategies for advancement in software. This innovative publication presents a significant resource to assist project managers, engineers, and developers interested in experimenting with new approaches in software expansion.

Early estimation of software size in object-oriented environments a case study in a CMM level 3 software firm

Early estimation of the size of a software product is extremely important. In this paper we analyze two software packages developed by a CMM level 3 software firm. We study if any property of analysis objects can be used to infer the size of the final code in an object-oriented environment. In both cases we find the number of methods well correlated with software size, in the sense that the correlation with the final size is high (r>0.77) and significant at the level 0.05. Inferential statistics guarantee that the results of this study are also applicable outside the scope of the two projects.