We propose an approach for complex software analysis based on visualization. Our work is motivated by the fact that in spite of years of research and practice, software development and maintenance are still time and resource consuming, and high-risk activities. The most important reason in our opinion is the complexity of many phenomena related to software, such as its evolution and its reliability. In fact, there is very little theory explaining them. Today, we have a unique opportunity to empirically study these phenomena, thanks to large sets of software data available through open-source programs and open repositories. Automatic analysis techniques, such as statistics and machine learning, are usually limited when studying phenomena with unknown or poorlyunderstood influence factors. We claim that hybrid techniques that combine automatic analysis with human expertise through visualization are excellent alternatives to them. In this paper, we propose a visualization framework that supports quality analysis of large-scale software systems. We circumvent the problem of size by exploiting perception capabilities of the human visual system. Categories and Subject Descriptors D.2.8 [Software Engineering]: Metrics—complexity measures, product metrics; D.1.5 [Programming Techniques]:

Some free software projects have been extremely successful. This rise to prominence can be attributed to the high quality and suitability of the software. This quality and suitability is achieved through an elaborate peer-review process performed by a large community of users, who act as co-developers to identify and correct software defects and add features. Although this process is crucial to the success of free software projects, there is more to the free software development than the creation of a ‘bazaar’. In this paper we draw on existing free software projects to define a lifecycle model for free software. This paper then explores each phase of the lifecycle model and agrees that, while the bazaar phase attracts the most attention, it is the initial modular design that accommodates diverse interventions. Moreover, it is the period of transition from the initial group to the larger community based development that is crucial in determining whether a free software project will succeed or fail. 2

Code cloning is not only assumed to inflate maintenance costs but also considered defect-prone as inconsistent changes to code duplicates can lead to unexpected behavior. Consequently, the identification of duplicated code, clone detection, has been a very active area of research in recent years. Up to now, however, no substantial investigation of the consequences of code cloning on program correctness has been carried out. To remedy this shortcoming, this paper presents the results of a large-scale case study that was undertaken to find out if inconsistent changes to cloned code can indicate faults. For the analyzed commercial and open source systems we not only found that inconsistent changes to clones are very frequent but also identified a significant number of faults induced by such changes. The clone detection

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Abstract. To date, Semantic Web research has tended to focus on data modelling challenges, at the expense of software architecture and engineering issues. Our empirical analysis shows that implementing Semantic Web technologies creates challenges which can affect the whole application. Standard solutions and best practices for Semantic Web technologies are just emerging. The lack of these has been an obstacle for implementing and deploying applications which exploit Semantic Web technologies for real world use cases. In this paper we conduct an empirical survey of Semantic Web applications. We use this empirical data to propose a reference architecture for Semantic Web applications, and to identify the four main challenges for implementing the most common functionality related to Semantic Web technologies from a software engineering perspective: (i) the issues involved in integrating noisy and heterogeneous data, (ii) the mismatch of data models and APIs between components, (iii) immature and belated best practices and standards, and (iv) the distribution of application logic across components. We describe two orthogonal approaches for mitigating these challenges: (a) simplifying the application architecture by delegating generic functionality to external service providers, and (b) assembling and customising of components provided by software frameworks for rapid development of complete applications. 1

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be found below).

With the maturity of information and communication technologies, offshore development of software by outsourcers is a new trend for reshaping IT strategy around the globe. Technological advances have increased the interconnection between different societies, facilitating a continuous software development cycle or follow-the-sun approach by having team members located in different geographical settings. Software development is an iterative process, in which knowledge builds with the progression of software development work and requires an ongoing awareness by team members of all the changing definitions and relationships in the development effort. This poses a bigger challenge in a global environment as the software development processes happen in a dynamic and distributed setting. New Zealand and India are both exemplars of the emerging offshore software producer market, and hence a study of their offshore software development processes forms a basis of this research study. These issues are illustrated using three case studies of offshore software providers in New Zealand and India. The case study data reveals that these firms emphasize on different drivers for success in their work practices as they compete as outsourcing destinations.

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