Requirements engineering is a crucial phase of software engineering, and requirements prioritization is an essential stage of requirements engineering particularly in agile software development. Requirements prioritization goals at eliciting which requirements of software need to be covered in a particular release. The key point is which requirement will be selected in the next iteration and which one will be delayed to other iterations for minimizing risk during development and meeting stakeholders’ needs. There are many existing techniques for requirement prioritization, but most of these techniques do not cover continuous growth and change of requirements or cover requirements dependencies. So, most of these prioritization techniques need to be more continuous, scalable, implemented merely and integrated with software development life cycle and not work separately. This paper introduces a framework to prioritize requirements in agile software development. This framework tries to find solutions for the challenges facing this prioritization process such as how to make this prioritization continuous and scalable and how to deal with rapidly requirement changes and its dependencies.

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Information that are represented as text are either facts or opinions, whenever we need to make a decision, we often seek out the opinions of others which is one of the most influencing factors for our decisions. Traditionally, individuals can get opinions from friends and family while organizations use surveys, focus groups, opinion polls and consultants. Nowadays, opinions expressed through user generated content are considered as one of the important types of information which is available on the web, therefore, many resources have been emerged for expressing opinions including social media and others. This situation has revealed the necessity for robust, flexible Information Extraction (IE) systems, these systems have the availability to transform the web pages into program-friendly structures such as a relational database to reveal these opinions. In this paper, we propose an approach to classify the opinions of a document or a set of documents considering an object. The approach has been implemented and applied on a dataset of opinions. The proposed system discover the opinions provided for an object in a document or set of documents. The system discovers different types of opinionated statements, including the opinionated, comparative, superlative, and non-opinionated. The system has been applied on a set of 4000 sentences, and the results has been evaluated using the standard metrics, they are True positive, True negative, False positive, False negative, Precision, Recall, and F-score. We also provided a comparison of the presented work with previous work that has been presented in the same field.

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Abstract:In the last few decades SOA (Service Oriented Architecture) has become the new trend in the IT industry. Many organizations tend to migrate to SOA in order to cope with the rapidly changing business. Effort estimation of SOA projects has become a real challenge to project managers due to the limited literatures addressing this issue. The traditional effort estimation techniques do not fit SOA projects entirely, as SOA has unique characteristics were not addressed by the traditional cost estimation approaches. These unique SOA characteristics include: loose coupling, reusability, composability and discoverability. On the other hand, cost estimation approaches that were proposed to estimate SOA projects, are still immature and most of them are impractical. They cannot be used in real life projects, as they are more guidelines than actual practical cost estimation approaches. This paper proposes an effort estimation approach for SOA projects that has been applied to different variety of services. It considers SOA characteristics and the various cost factors for different types of services including available, migrated, new and composed services. This proposed approach provides effort estimation technique for each type of service. The proposed approach also gives effort distribution among project phases for easily resources allocation. This framework has been applied to real life projects in the IT industry as the SOA project is divided into its component services and each service is estimated solely based on its type. The services' efforts are then aggregated to calculate the project's overall effort. The estimated effort relative error in the case studies ranges from 3.66 % and 19.14%.