Investigating Role of Data Mining in Software Engineering

  Companies that focus on software development produce vast volumes of data. Every stage of software development, from gathering requirements to ongoing upkeep, generates its own set of data. To better the software, efforts are undertaken to collect and store data produced in software repositories. Data mining techniques are used to the massive amounts of data found in software repositories in order to extract previously unseen patterns and insights. Researchers from the fields of Software Engineering and Data Mining have lately made this area of study a top priority. This research aims to examine the many uses of data mining in software engineering, the many types of software engineering data that can be mined, and the many data mining techniques that are available and have been used by researchers to solve the problems that this research focuses on. The next step is to use this classification to determine which subfield within software engineering has the highest scholarly interest.   &nbsp

A classification of RE papers:(A)re we researching or designing RE techniques?

Discussion of a paper in RE program committees is often\ud complicated by lack of agreement about evaluation criteria\ud to be applied to the paper. For some years now, successive\ud program chairs have attempted to increase clarity by\ud including a paper classification in their CFP, and making the\ud evaluation criteria per paper class explicit. This short note\ud presents a paper classification based on this experience. It\ud can be used as guide by program chairs. It can also be used\ud by authors as well as reviewers to understand what kind of\ud paper they are writing or reviewing, and what criteria should\ud be applied in evaluating the paper

Requirements Prioritization Based on Benefit and Cost Prediction: An Agenda for Future Research

In early phases of the software cycle, requirements prioritization necessarily relies on the specified requirements and on predictions of benefit and cost of individual requirements. This paper presents results of a systematic review of literature, which investigates how existing methods approach the problem of requirements prioritization based on benefit and cost. From this review, it derives a set of under-researched issues which warrant future efforts and sketches an agenda for future research in this area

An Analysis of Service Ontologies

Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work