Systematizing requirements elicitation technique selection

ContextThis research deals with requirements elicitation technique selection for software product requirements and the overselection of open interviews.ObjectivesThis paper proposes and validates a framework to help requirements engineers select the most adequate elicitation techniques at any time.MethodWe have explored both the existing underlying theory and the results of empirical research to build the framework. Based on this, we have deduced and put together justified proposals about the framework components. We have also had to add information not found in theoretical or empirical sources. In these cases, we drew on our own experience and expertise.ResultsA new validated approach for requirements technique selection. This new approach selects techniques other than open interview, offers a wider range of possible techniques and captures more requirements information.ConclusionsThe framework is easily extensible and changeable. Whenever any theoretical or empirical evidence for an attribute, technique or adequacy value is unearthed, the information can be easily added to the framework.     

The state of the art in automated requirements elicitation

ContextIn large software development projects a huge number of unstructured text documents from various stakeholders becomes available and needs to be analyzed and transformed into structured requirements. This elicitation process is known to be time-consuming and error-prone when performed manually by a requirements engineer. Consequently, substantial research has been done to automate the process through a plethora of tools and technologies.ObjectiveThis paper aims to capture the current state of automated requirements elicitation and derive future research directions by identifying gaps in the existing body of knowledge and through relating existing works to each other. More specifically, we are investigating the following research question: What is the state of the art in research covering tool support for automated requirements elicitation from natural language documents?MethodA systematic review of the literature in automated requirements elicitation is performed. Identified works are categorized using an analysis framework comprising tool categories, technological concepts and evaluation approaches. Furthermore, the identified papers are related to each other through citation analysis to trace the development of the research field.ResultsWe identified, categorized and related 36 relevant publications. Summarizing the observations we made, we propose future research to (1) investigate alternative elicitation paradigms going beyond a pure automation approach (2) compare the effects of different types of knowledge on elicitation results (3) apply comparative evaluation methods and multi-dimensional evaluation measures and (4) strive for a closer integration of research activities across the sub-fields of automatic requirements elicitation.ConclusionThrough the results of our paper, we intend to contribute to the Requirements Engineering body of knowledge by (1) conceptualizing an analysis framework for works in the area of automated requirements elicitation, going beyond former classifications (2) providing an extensive overview and categorization of existing works in this area (3) formulating concise directions for future research.     

Requirement-driven Architecture for Learning Analytics: The Case of AT41 Project

Digital technologies are becoming present and essential in all sectors of our lives. In education, the intensive usage of digital learning devices contributes to generating a large amount of trace data from digital learning activities. Intelligent exploitation of these traces represents a valuable asset for both device producers (to improve the design of the devices) and consumers (learners and teachers). In this paper, we first share our vision for better exploitation by teachers, of traces from middle schoolers' digital activities generated by their use of tools and digital learning services during different classes. This vision is a part of the AT41 project funded by the French Ministry of Education. This exploitation has to meet the requirements of the different teachers. Conducting such a project is not an easy task, because it has to consider the following issues: the lack of comprehensive and clear methodology to design and exploit these traces; ②heterogeneity of teacher requirements that complicates their elicitation and analysis; ③the diversity of trace sources. Secondly, we propose a requirement-driven architecture for Learning Analytics composed of a well-identified life cycle. This architecture is augmented by learner traces. It offers a repository storing both teacher requirements and traces to facilitate the Learning Analytics in generating relevant and valuable indicators.     

A framework to improve communication during the requirements elicitation process in GSD projects

Achieving a shared understanding of requirements is difficult in any situation, even more so in global software development projects. In such environments, people must deal not only with the lack of face to face communication, but also with other issues such as time difference, cultural diversity and a large amount of information originating from different sources throughout the world. Obtaining the right requirements therefore implies extra effort. In order to minimize such problems, we propose a framework that focuses on analyzing the factors that may be problematic in global software development and which suggests a set of strategies to improve the requirements elicitation process in such environments. In this paper, we describe the different phases of our framework and present the results of an experiment that test part of this framework. The results indicate that applying some of the strategies proposed in the framework seems to positively affect the stakeholders’ satisfaction with regard to communication. Moreover, the quality of the written software requirements specifications seems to be better as well when using those strategies.     

Evaluating cloud deployment scenarios based on security and privacy requirements

Migrating organisational services, data and application on the Cloud is an important strategic decision for organisations due to the large number of benefits introduced by the usage of cloud computing, such as cost reduction and on-demand resources. Despite, however, many benefits, there are challenges and risks for cloud adaption related to (amongst others) data leakage, insecure APIs and shared technology vulnerabilities. These challenges need to be understood and analysed in the context of an organisation’s security and privacy goals and relevant cloud computing deployment models. Although the literature provides a large number of references to works that consider cloud computing security issues, no work has been provided, to our knowledge, which supports the elicitation of security and privacy requirements and the selection of an appropriate cloud deployment model based on such requirements. This work contributes towards this gap. In particular, we propose a requirements engineering framework to support the elicitation of security and privacy requirements and the selection of an appropriate deployment model based on the elicited requirements. Our framework provides a modelling language that builds on concepts from requirements, security, privacy and cloud engineering, and a systematic process. We use a real case study, based on the Greek National Gazette, to demonstrate the applicability of our work.     

Improving requirements elicitation: an empirical investigation of procedural prompts

Abstract.  Information system success is dependent upon the effectiveness of requirements elicitation. Requirements elicitation is subject to numerous challenges, however, including cognitive limitations of analysts. In the present study, we test prompts designed to overcome the cognitive limitations that cause analysts to gather inadequate and inaccurate requirements. The study's results indicate that providing analysts with procedural prompts to aid their requirements elicitation can result in the acquisition of additional meaningful requirements. In addition, the procedural prompts designed to mitigate cognitive challenges were significantly more effective than simple interrogatory prompts. Theoretical implications for the elicitation of requirements and practical implications for the training and practice of systems analysts are discussed.     

A Communication Framework for Digital Libraries

Digital libraries involve various types of data like text, audio, images and video. The data objects are typically very large and of the order of hundreds and thousands of kilobytes. In a digital library, these data objects are distributed in a wide area network. Retrieving large data objects in a wide area network has a high response time. We have conducted experiments to measure the communication overhead in the response time. We have studied the correlation between communication and size of data, between communication and type of data and the communication delay to various sites in a local and wide area network. We present different strategies for reducing delay while communicating multimedia data. Images are amenable to losing data without losing semantics of the image. Lossy compression techniques reduce the quality of the image and reduce the size leading to a lower communication delay. We compared the communication delay between compressed and uncompressed images and study the overhead due to compression and decompression. We present issues in providing digital library service to mobile users and discuss a question: What if communication were free? Finally, we present a framework for efficient communication of digital library data.

     

电子图书馆多媒体信息传输服务质量管理的研究

该文在浏览器/服务器环境下建立了一个数字化图书馆多媒体数据流同步传输的管理方案。定义了多媒体对象、任务、同步化传输约束条件以及相应的QOS评价指标,基于上述方案及评价指标,给出了数字化图书馆多媒体流同步传输的控制算法以及相应的实验结果。     

An engineering process for developing Secure Data Warehouses

We present a new approach for the elicitation and development security requirements in the entire Data Warehouse (DWs) life cycle, which we have called a Secure Engineering process for DAta WArehouses (SEDAWA). Whilst many methods for the requirements analysis phase of the DWs have been proposed, the elicitation of security requirements as non-functional requirements has not received sufficient attention. Hence, in this paper we propose a methodology for the DW design based on Model Driven Architecture (MDA) and the standard Software Process Engineering Metamodel Specification (SPEM) from the Object Management Group (OMG). We define four phases comprising of several activities and steps, an d five disciplines which cover the whole DW design. Our methodology adapts the i¹ framework to be used under MDA and the SPEM approaches in order to elicit and develop security requirements for DWs. The benefits of our proposal are shown through an example related to the management of the pharmacies consortium business.     

Modular multi-channel data acquisition systems

A flexible approach to complexity-reduced multi-channel data acquisition from a large quantity of sensors, essential for connecting computers with real world objects, is discussed and the obtained experience in this area is summarized. Data acquisition from wideband, event timing, and large distributed clusters of signal sources are discussed with emphasis on methods and algorithms providing for data gathering from large sensor systems. We discuss special signal digitizing techniques, including pseudorandomized multiplexing, time-to-digital conversions, and signal sample value-taking at time instants when the input signal crosses a sinusoidal reference function. The versatility of the data acquisition systems is achieved by using modular system design. To achieve the maximum from the suggested data acquisition technology, the acquired data processing is based on the theory of digital alias-free signal processing. The text was submitted by the authors in English.     

高帧频二维数字图像数据采集速率控制系统设计

为解决传统数据采集速率控制系统存在的采集速率较低,采集精度较低等问题,提出高帧频二维数字图像数据采集速率控制系统设计。充分考虑数据采集速率控制需求,选用KPCI-811数据采集卡对系统硬件部分的数据采集电路和电源电路进行改进,优化软件部分的数据采集、数据过滤及数据采集效率控制功能,完成高帧频二维数字图像数据采集速率控制系统的设计。实验结果表明,较传统系统,该系统的采集耗时更少,采集速率更高,采集精度更高,满足数据采集速率控制需求。     

适于底层协议栈开发的数据采集与仿真系统

针对数字通信系统中底层协议栈开发过程中处理数据量大,出现问题不易再现、难于追踪的问题,设计了一种专门用于底层协议栈开发的高速数据采集、仿真系统。系统采用USB总线作为高速数据通路,使用FPGA进行格式转换及数据缓冲。论述了仿真系统的工作原理和系统框架,分析了数据转换、解析的流程,给出了系统仿真的一般模式。     

Using remote sensing for monitoring of autumn tillage in Norway

Management systems on agricultural land in Norway are causing concern because of increasing area wide soil erosion, consequent increase in sediment loads and nutrient losses to waters, and their consequent pollution. Monitoring of areas in autumn is important because this is the start of a season when much of the erosion occurs. This is often caused by management systems in autumn, but also because climatic conditions in this season are important for erosion processes.

We have investigated several sources of remote sensing data, with a view to assembling the best overall monitoring system for this geoscience problem. The sources were digitised CIR (colour infrared pseudocolour) aerial photography, SPOT and ERS-1 SAR. CIR photography proved more accurate than SPOT data, especially with regard to exposed soils as result of CIR's continuous spectral sensitivity. We found that SPOT is clearly limited as a monitoring tool for soils and there is a need for better sensors in range 680 to 790 nm wavelengths.

ERS-1 SAR provides information when the optical sources cannot, but is dependant on good digital elevation models. We found that the most effective monitoring is done using a combination of microwave and optical sources.     

Effective Communication in Requirements Elicitation: A Comparison of Methodologies

The elicitation or communication of user requirements comprises an early and critical but highly error-prone stage in system development. Socially oriented methodologies provide more support for user involvement in design than the rigidity of more traditional methods, facilitating the degree of user–designer communication and the ‘capture’ of requirements. A more emergent and collaborative view of requirements elicitation and communication is required to encompass the user, contextual and organisational factors. From this accompanying literature in communication issues in requirements elicitation, a four-dimensional framework is outlined and used to appraise comparatively four different methodologies seeking to promote a closer working relationship between users and designers. The facilitation of communication between users and designers is subject to discussion of the ways in which communicative activities can be ‘optimised’ for successful requirements gathering, by making recommendations based on the four dimensions to provide fruitful considerations for system designers.     

Effective Hybrid Content-Based Collaborative Filtering Approach for Requirements Engineering

Requirements engineering (RE) is among the most valuable and critical processes in software development. The quality of this process significantly affects the success of a software project. An important step in RE is requirements elicitation, which involves collecting project-related requirements from different sources. Repositories of reusable requirements are typically important sources of an increasing number of reusable software requirements. However, the process of searching such repositories to collect valuable project-related requirements is time-consuming and difficult to perform accurately. Recommender systems have been widely recognized as an effective solution to such problem. Accordingly, this study proposes an effective hybrid content-based collaborative filtering recommendation approach. The proposed approach will support project stakeholders in mitigating the risk of missing requirements during requirements elicitation by identifying related requirements from software requirement repositories. The experimental results on the RALIC dataset demonstrate that the proposed approach considerably outperforms baseline collaborative filtering-based recommendation methods in terms of prediction accuracy and coverage in addition to mitigating the data sparsity and cold-start item problems.     

Incremental application of knowledge to continuously arriving time-oriented data

In our previous work, we introduced a computational architecture that effectively supports the tasks of continuous monitoring and of aggregation querying of complex domain meaningful time-oriented concepts and patterns (temporal abstractions), in environments featuring large volumes of continuously arriving and accumulating time-oriented raw data. Examples include provision of decision support in clinical medicine, making financial decisions, detecting anomalies and potential threats in communication networks, integrating intelligence information from multiple sources, etc. In this paper, we describe the general, domain-independent but task-specific problem-solving method underling our computational architecture, which we refer to as incremental knowledge-based temporal abstraction (IKBTA). The IKBTA method incrementally computes temporal abstractions by maintaining persistence and validity of continuously computed temporal abstractions from arriving time-stamped data. We focus on the computational framework underlying our reasoning method, provide well-defined semantic and knowledge requirements for incremental inference, which utilizes a logical model of time, data, and high-level abstract concepts, and provide a detailed analysis of the computational complexity of our approach.     

Empirical evidence for the usefulness of Armstrong relations in the acquisition of meaningful functional dependencies

Armstrong relations satisfy precisely those data dependencies that are implied by a given set of data dependencies. A common perception is that Armstrong relations are useful in the acquisition of data semantics, in particular since errors during the requirements elicitation have the most expensive consequences.     

A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

Nowadays, industrial companies are facing ever-increasing challenges to generate new value-in-use and maintain their high competitiveness in the market. With the rapid development of Information and Communication Technology (ICT), IT is embedded in the products themselves, i.e. smart, connected products (SCPs) to generate values. Hence, an emerging value proposition paradigm, smart product-service system (Smart PSS) was introduced, by leveraging both SCPs and its generated services as a solution bundle to meet individual customer needs. Unlike other types of PSS, in Smart PSS, massive user-generated data and product-sensed data are collected during the usage phase, where potential requirements can be elicited readily in a value co-creation manner with context-awareness. Nevertheless, only few scholars discuss any systematic manner to support requirement elicitation in such context. To fill the gaps, this research proposes a novel data-driven graph-based requirement elicitation framework in the Smart PSS, so as to assist engineering/designers make better design improvement or new design concept generation in a closed-loop manner. It underlines the informatics-based approach by integrating heterogeneous data sources into a holistic consideration. Moreover, by leveraging graph-based approach, context-product-service information can be linked by the edges and nodes in-between them to derive reliable requirements. To validate its feasibility and advantages, an illustrative example of smart bicycle design improvement is further adopted. As an explorative study, it is hoped that this work provides useful insights for the requirement elicitation process in today’s smart connected environment.     

Assumptions implicit in remote sensing data acquisition and analysis

Abstract

The literature contains many examples of image acquisition and analysis which have been inappropriately applied and which have led to empirical results which may not be reproducible, or which are not conclusive. In this paper, we deal with eleven major assumptions which are implicit in the acquisition and in the analysis of passively sensed digital image data. It is hoped that an enumeration of such assumptions might lead to improved rules for image acquisition and analysis.