International Journal of Software Engineering and Knowledge Engineering

The adoption of innovative Software Engineering (SE) processes by an organization implies that engineers have to learn new processes which they might not be familiar with. Social software can support and enhance this adoption process, so research needs to focus on how the exchange of knowledge among software engineers using these tools can help to perform training more effectively. We propose a framework based on social software to support the collaborative learning, adoption and improvement of SE processes through the exchange of experiences among individuals. This article examines factors influencing the adoption of new SE processes and the quality of the experiences shared using the proposed framework in comparison with similar ones. Two case studies were carried out involving junior engineers in a training course on agile software development. Anonymous surveys collected data on the perceived quality of the experiences shared during the research, their usefulness, and the simplicity of the mechanisms provided to contribute experiences. Results show that the adoption of new SE processes is influenced by several factors such as the commitment of software engineers to collaborate in the adoption of the new process, the perceived level of usefulness of the tacit knowledge elicited during the adoption process, the diversity of the topics covered by the shared knowledge, the simplicity of the mechanisms to contribute new tacit knowledge, and the amount of learning achieved by software engineers.

The growing interest of software companies for improving their internal processes, not just software development processes, but also processes in other domains such as Information Technology (IT) service management or information security management, has encouraged these companies to implement recognized models or standards. Most of the ISO standards that define models for software quality, IT service management or information security management provide their recommendations, guidelines, requirements or good practices under a process approach. Due to this approach, there are a large number of relations between these models as well as many common elements. From the study of these relations, this paper presents MIN-ITs, a new framework that supports the integration of different ISO standards related to IT management.

Organizational software processes improvement offers a key opportunity for organizations to be more efficient and effective. However, in most cases software process improvement initiatives in organizations become a path full of obstacles. As a consequence, organizations worldwide are adopting international standards and models in an effort to improve their software processes. Nevertheless, the difficulty of using multi-model improvement environments for the implementation of software processes improvements is well-known. In this context, effective integration of models and standards is a tool that enhances information sharing and communication. Integration can play a crucial role for the implementation of multi-model environments in order to be used as a reference model in software process improvements. This paper shows a methodology that enables organizations to establish a multi-model environment based on their business goals and on the results of a case study focused on implementing improvements in project management processes. Finally, results obtained after applying the methodology and future research line related to a platform for providing knowledge management and information sharing are included.

Software companies have to manage different software projects based on different time, cost, and manpower requirement, which is a very complex task in software project management. Accurate software estimates at the early phase of software development is one of the crucial objectives and a great challenge in software project management, in the last decades. Since software development attributes are vague and uncertain at the early phase of development, software estimates tend to a certain degree of estimation error. A software development cost estimation model incorporates soft computing techniques provides a solution to fit the vagueness and uncertainty of software attributes. In this paper, an adaptive artificial neural network (ANN) architecture for Constructive Cost Model (COCOMO) is proposed in order to produce accurate software estimates. The ANN is utilized to determine the importance of calibration of the software attributes using past project data in order to produce accurate software estimates. Software project data from the COCOMO I and NASA'93 data sets were used in the evaluation of the proposed model. The result shows an improvement in estimation accuracy of 8.36% of the ANN-COCOMO II when compared with the original COCOMO II.

Providing efficient mining algorithm to discover recent frequent XML user query patterns is crucial, as many applications use XML to represent data in their disciplines over the Internet. These recent frequent XML user query patterns can be used to design an index mechanism or cached and thus enhance XML query performance. Several XML query pattern stream mining algorithms have been proposed to record user queries in the system and thus discover the recent frequent XML query patterns over a stream. By using these recent frequent XML query patterns, the query performance of XML data stream is improved. In this paper, user queries are modeled as a stream of XML queries and the recent frequent XML query patterns are thus mined over the stream. Data-stream mining differs from traditional data mining since its input of mining is data streams, while the latter focuses on mining static databases. To facilitate the one-pass mining process, novel schemes (i.e. XstreamCode and XstreamList) are devised in the mining algorithm (i.e. X²StreamMiner) in this paper. X²StreamMiner not only reduces the memory space, but also improves the mining performance. The simulation results also show that X²StreamMiner algorithm is both efficient and scalable. There are two major contributions in this paper. First, the novel schemes are proposed to encode and store the information of user queries in an XML query stream. Second, based on the two schemes, an efficient XML query stream mining algorithm, X²StreamMiner, is proposed to discover the recent frequent XML query patterns.