Improving the detection of requirements discordances among stakeholders

This paper introduces a technique to identify requirements discordances among stakeholders. This technique is validated in experiments. An extended version of the goal-oriented requirements elicitation method, named attributed goal-oriented analysis (AGORA), and its supporting tool are used. Two types of requirements discordances among stakeholders are defined: the first arises from the different interpretations by the stakeholders and the second is the result of different evaluations of preferences. Discordances are detected by the preference matrices in AGORA. Each preference matrix represents both preferences of each stakeholder and the estimated preferences of other stakeholders. A supporting tool for the AGORA method was developed. This tool is a groupware that seamlessly combines face-to-face meetings for goal elicitation and distributed individual sessions for scoring preference values. The experimental results showed that the proposed classification of discordances was sound and that the occurrences of the requirements discordances could be detected by preference matrices.     

Towards automated requirements prioritization and triage

Time-to-market deadlines and budgetary restrictions require stakeholders to carefully prioritize requirements and determine which ones to implement in a given product release. Unfortunately, existing prioritization techniques do not provide sufficient automation for large projects with hundreds of stakeholders and thousands of potentially conflicting requests and requirements. This paper therefore describes a new approach for automating a significant part of the prioritization process. The proposed method utilizes data-mining and machine learning techniques to prioritize requirements according to stakeholders’ interests, business goals, and cross-cutting concerns such as security or performance requirements. The effectiveness of the approach is illustrated and evaluated through two case studies based on the requirements of the Ice Breaker System, and also on a set of stakeholders’ raw feature requests mined from the discussion forum of an open source product named SugarCRM.     

Improved practical support for large-scale requirements prioritising

An efficient, accurate and practical process for prioritising requirements is of great importance in commercial software developments. This article improves an existing cost-value approach in which stakeholders compare all unique pairs of candidate requirements according to their value and their cost of implementation. Techniques for reducing the required number of comparisons are suggested, thus making the process more efficient. An initial approach for managing requirements interdependencies is proposed. A support tool for the improved process has been developed to make the process more practical in commercial developments. The improved process and its support tool have been applied and evaluated in an industrial project at Ericsson Radio Systems AB. The results indicate a pressing need for mature processes for prioritising requirements, and the work presented here is an important step in that direction.     

What stakeholders will or will not say: A theoretical and empirical study of topic importance in Requirements Engineering elicitation interviews

Interviewing stakeholders is a way to elicit information about requirements for a system-to-be. A difficulty when preparing such elicitation interviews is to select the topics to discuss, so as to avoid missing important information. Stakeholders may spontaneously share information on some topics, but remain silent on others, unless asked explicitly. We propose the Elicitation Topic Map (ETM) to help engineers in preparing interviews. ETM is a diagram showing topics that may be discussed during interviews, and shows how likely stakeholders discuss each of these topics spontaneously. If a topic is less likely to be discussed spontaneously, then this suggests that engineers may want to prepare questions on it, before the interview. ETM was produced through theoretical and empirical research. The theoretical part consisted of identifying topic sets based on a conceptual model of communication context, grounded in philosophy, artificial intelligence, and computer science. The empirical part involved interviews with Requirements Engineering professionals to identify the topic sets and topics in each set, surveys of business people in order to evaluate how likely they would spontaneously share information about topics, and evaluations of how likely students would share information about each topic, when asked about requirements for social network websites.     

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.     

A methodology for the classification of quality of requirements using machine learning techniques

ContextOne of the most important factors in the development of a software project is the quality of their requirements. Erroneous requirements, if not detected early, may cause many serious problems, such as substantial additional costs, failure to meet the expected objectives and delays in delivery dates. For these reasons, great effort must be devoted in requirements engineering to ensure that the project’s requirements results are of high quality. One of the aims of this discipline is the automatic processing of requirements for assessing their quality; this aim, however, results in a complex task because the quality of requirements depends mostly on the interpretation of experts and the necessities and demands of the project at hand.ObjectiveThe objective of this paper is to assess the quality of requirements automatically, emulating the assessment that a quality expert of a project would assess.MethodThe proposed methodology is based on the idea of learning based on standard metrics that represent the characteristics that an expert takes into consideration when deciding on the good or bad quality of requirements. Using machine learning techniques, a classifier is trained with requirements earlier classified by the expert, which then is used for classifying newly provided requirements.ResultsWe present two approaches to represent the methodology with two situations of the problem in function of the requirement corpus learning balancing, obtaining different results in the accuracy and the efficiency in order to evaluate both representations. The paper demonstrates the reliability of the methodology by presenting a case study with requirements provided by the Requirements Working Group of the INCOSE organization.ConclusionsA methodology that evaluates the quality of requirements written in natural language is presented in order to emulate the quality that the expert would provide for new requirements, with 86.1 of average in the accuracy.     

Identified adjustability dimensions when generating a product specific requirements specification by requirements reuse

A requirements reuse setups typically includes reusable requirement set(s) containing a collection of reusable requirements and a number of product specific requirements sets which are drawn from the reusable set(s). The ideal scenario when reusing requirements is that all the product requirements can be drawn directly from the reusable set. However, this is rarely the case in product development as new requirements are likely to surface. A critical issue in requirements reuse therefore becomes how to enable products to efficiently reuse requirements as well incorporating changes to the product set. In this paper the objective is not to present a specific method for requirements reuse but to introduce and discuss the possible dimensions of adjustability when generating a product requirement set by reusing requirements from a reusable set. Six adjustability dimensions have been identified. An extensive state of the art is included to introduce the presented methods related to each adjustability dimensions. The options for implementing each adjustability dimensions in a requirement reuse approach are illustrated along with a discussion regarding the benefits and issues resulting from each option. This discussion should help practitioners to better understand the possible methods that can be implemented and to design a user friendly and sustainable approach. A case study, describing how the dimensions are incorporated in two requirements reuse approaches, for Danfoss Solar Inverters (SI) and Danfoss Frequency Drives is provided. As a result an overview of how each adjustability dimensions is implemented in each case is presented. The case study demonstrates that all the identified adjustability dimensions were important elements in requirements reuse implementation. The case study furthermore highlights the need, not only to understand the effects of each adjustability dimension but also of the dependencies to case specific criterions. The classification of adjustability dimensions in requirements reuse and the options for their implementation has not been outlined by previous research and should be a useful contribution both to researchers and practitioners working in the field of requirements reuse.     

Stakeholder viewpoints in requirements definition: A framework for understanding viewpoint development approaches

Requirements definition is a critical activity within information systems development. It involves many stakeholder groups: managers, various end-users and different systems development professionals. Each group is likely to have its own viewpoint representing a particular perspective or set of perceptions of the problem domain. To ensure as far as possible that the system to be implemented meets the needs and expectations of all involved stakeholders, it is necessary to understand their various viewpoints and manage any inconsistencies and conflicts. Viewpoint development during requirements definition is the process of identifying, understanding and representing different viewpoints. This paper proposes a conceptual framework for understanding and investigating viewpoint development approaches. Results of the use of the framework for a comparison of viewpoint development approaches are discussed and some important issues and directions for future research are identified.     

Deriving static and dynamic concepts from software requirements using sophisticated tagging

Natural language requirements specifications form the basis for the subsequent phase of the information system development process, namely the development of conceptual schemata. Both, the textual as well as the conceptual representations are not really appropriate for being thoroughly captured and validated by the ‘requirement holders’, i.e. the end users. Therefore, in our approach the textual specifications are firstly linguistically analyzed and translated into a so-called conceptual predesign schema. That schema is formulated using an interlingua which is based on a lean semantic model, thus allowing users to participate more efficiently in the design and validation process. After validation, the predesign schema is mapped to a conceptual representation (e.g. UML). The sequence of these translation and transformation steps is described by the “NIBA workflow”. This paper focuses on the information supporting a step by step mapping of natural language requirements specifications to a conceptual model, and on how that information is gained. On particular, we present a four-level interpretation of tagging-output.     

Comparing the performance of metaheuristics for the analysis of multi-stakeholder tradeoffs in requirements optimisation

Context

In requirements engineering, there will be many different stake holders. Often the requirements engineer has to find a set of requirements that reflect the needs of several different stake holders, while remaining within budget.

Objective

This paper introduces an optimisation-based approach to the automated analysis of requirements assignments when multiple stake holders are to be satisfied by a single choice of requirements.

Method

The paper reports on experiments using two different multi-objective evolutionary optimisation algorithms with real world data sets as well as synthetic data sets. This empirical validation includes a statistical analysis of the performance of the two algorithms.

Results

The results reveal that the Two-Archive algorithm outperformed the others in convergence as the scale of problems increase. The paper also shows how both traditional and animated Kiviat diagrams can be used to visualise the tensions between the stake holders’ competing requirements in the presence of increasing budgetary pressure.

Conclusion

This paper presented the concept of internal tensioning among multi-stakeholder in requirements analysis and optimisation for the first time. This analysis may be useful in internal negotiations over budgetary allowance for the project.     

A systematic literature review of software requirements prioritization research

ContextDuring requirements engineering, prioritization is performed to grade or rank requirements in their order of importance and subsequent implementation releases. It is a major step taken in making crucial decisions so as to increase the economic value of a system.ObjectiveThe purpose of this study is to identify and analyze existing prioritization techniques in the context of the formulated research questions.MethodSearch terms with relevant keywords were used to identify primary studies that relate requirements prioritization classified under journal articles, conference papers, workshops, symposiums, book chapters and IEEE bulletins.Results73 Primary studies were selected from the search processes. Out of these studies; 13 were journal articles, 35 were conference papers and 8 were workshop papers. Furthermore, contributions from symposiums as well as IEEE bulletins were 2 each while the total number of book chapters amounted to 13.ConclusionPrioritization has been significantly discussed in the requirements engineering domain. However, it was generally discovered that, existing prioritization techniques suffer from a number of limitations which includes: lack of scalability, methods of dealing with rank updates during requirements evolution, coordination among stakeholders and requirements dependency issues. Also, the applicability of existing techniques in complex and real setting has not been reported yet.     

A specification pattern for use cases

In this paper, general formats and guidelines are proposed, in an attempt to ameliorate the impact of frequently observed difficulties during the specification of use cases generated using “natural language” for the documentation of system functionality. The various writing styles derived from the multiple grammatical alternatives found in the Spanish language and the terminological diversity that characterises this language tend to reduce the clarity of text in a use-case specification. Thus, the purpose of its use in the different stages of development in a software system or component is seriously affected. However, even if this study has been made specifically for the Spanish language, it could be easily generalised to any language whose sentences are of the form subject/predicate. In order to control these problems, the use of a specification pattern supported by a series of guidelines on style and terminology is proposed for drafting use cases. Additionally, various degrees of refinement are suggested to guide specifiers towards obtaining a use case written according to this pattern.     

Synergy between Activity Theory and goal/scenario modeling for requirements elicitation,analysis, and evolution

ContextIt is challenging to develop comprehensive, consistent, analyzable requirements models for evolving requirements. This is particularly critical for certain highly interactive types of socio-technical systems that involve a wide range of stakeholders with disparate backgrounds; system success is often dependent on how well local social constraints are addressed in system design.ObjectiveThis paper describes feasibility research, combining a holistic social system perspective provided by Activity Theory (AT), a psychological paradigm, with existing system development methodologies and tools, specifically goal and scenario modeling.MethodAT is used to understand the relationships between a system, its stakeholders, and the system’s evolving context. The User Requirements Notation (URN) is used to produce rigorous, analyzable specifications combining goal and scenario models. First, an AT language was developed constraining the framework for automation, second consistency heuristics were developed for constructing and analyzing combined AT/URN models, third a combined AT/URN methodology was developed, and consequently applied to a proof-of-concept system.ResultsAn AT language with limited tool support was developed, as was a combined AT/URN methodology. This methodology was applied to an evolving disease management system to demonstrate the feasibility of adapting AT for use in system development with existing methodologies and tools. Bi-directional transformations between the languages allow proposed changes in system design to be propagated to AT models for use in stakeholder discussions regarding system evolution.ConclusionsThe AT framework can be constrained for use in requirements elicitation and combined with URN tools to provide system designs that include social system perspectives. The developed AT/URN methodology can help engineers to track the impact on system design due to requirement changes triggered by changes in the system’s social context. The methodology also allows engineers to assess the impact of proposed system design changes on the social elements of the system context.     

Model-based requirements verification method: Conclusions from two controlled experiments

ContextRequirements engineering is one of the most important and critical phases in the software development life cycle, and should be carefully performed to build high quality and reliable software. However, requirements are typically gathered through various sources and are represented in natural language (NL), making requirements engineering a difficult, fault prone, and a challenging task.ObjectiveTo ensure high-quality software, we need effective requirements verification methods that can clearly handle and address inherently ambiguous nature of NL specifications. The objective of this paper is to propose a method that can address the challenges with NL requirements verification and to evaluate our proposed method through controlled experiments.MethodWe propose a model-based requirements verification method, called NLtoSTD, which transforms NL requirements into a State Transition Diagram (STD) that can help to detect and to eliminate ambiguities and incompleteness. The paper describes the NLtoSTD method to detect requirement faults, thereby improving the quality of the requirements. To evaluate the NLtoSTD method, we conducted two controlled experiments at North Dakota State University in which the participants employed the NLtoSTD method and a traditional fault checklist during the inspection of requirement documents to identify the ambiguities and incompleteness of the requirements.ResultsTwo experiment results show that the NLtoSTD method can be more effective in exposing the missing functionality and, in some cases, more ambiguous information than the fault-checklist method. Our experiments also revealed areas of improvement that benefit the method’s applicability in the future.ConclusionWe presented a new approach, NLtoSTD, to verify requirements documents and two controlled experiments assessing our approach. The results are promising and have motivated the refinement of the NLtoSTD method and future empirical evaluation.     

Empirical comparisons of animation and narration in requirements validation

Increasingly powerful computing technology suggests an expansion of multimedia features in requirements engineering methods. It is not obvious, however, that techniques such as animation and narration would improve the effectiveness of communicating domain information to stakeholders for validation. Three principles from the cognitive theory of multimedia learning (CTML) are used to compare validation methods using animation and narration with more traditional methods using static diagrams and text. Results suggest animation and narration can have significant positive impact on the level of domain understanding attained by participants. In particular, narration yielded strongly significant results. While these results should be viewed as preliminary, they indicate a potential advantage in the use of narration and possibly animation in requirements validation. The results provide justification for further research on the integration of multimedia techniques in developing and validating requirements.     

Reconciling software requirements and architectures with intermediate models

Little guidance and few methods are available for the refinement of software requirements into an architecture satisfying those requirements. Part of the challenge stems from the fact that requirements and architectures use different terms and concepts to capture the model elements relevant to each. In this paper we will present CBSP, a lightweight approach intended to provide a systematic way of reconciling requirements and architectures using intermediate models. CBSP leverages a simple set of architectural concepts (components, connectors, overall systems, and their properties) to recast and refine the requirements into an intermediate model facilitating their mapping to architectures. Furthermore, the intermediate CBSP model eases capturing and maintaining arbitrarily complex relationships between requirements and architectural model elements, as well as among CBSP model elements. We have applied CBSP within the context of different requirements and architecture definition techniques. We leverage that experience in this paper to demonstrate the CBSP method and tool support using a large-scale example.     

Towards the creation of a CNL adapted to requirements writing by combining writing recommendations and spontaneous regularities: example in a space project

The Quality Department of the French National Space Agency (CNES, Centre National d’Études Spatiales) wishes to design a writing guide based on the real and regular writing of requirements. As a first step in this project, the present article proposes a linguistic analysis of requirements written in French by CNES engineers. One of our goals is to determine to what extent they conform to several rules laid down in two existing Controlled Natural Languages (CNLs), namely the Simplified Technical English developed by the AeroSpace and Defense Industries Association of Europe and the Guide for Writing Requirements proposed by the International Council on Systems Engineering. Indeed, although CNES engineers are not obliged to follow any controlled language in their writing of requirements, we believe that language regularities are likely to emerge from this task, mainly due to the writers’ experience. We are seeking to identify these regularities in order to use them as a basis for a new CNL for the writing of requirements. The issue is approached using natural language processing tools to identify sentences that do not comply with the rules or contain specific linguistic phenomena. We further review these sentences to understand why the recommendations cannot (or should not) always be applied when specifying large-scale projects.     

Analysing anaphoric ambiguity in natural language requirements

Many requirements documents are written in natural language (NL). However, with the flexibility of NL comes the risk of introducing unwanted ambiguities in the requirements and misunderstandings between stakeholders. In this paper, we describe an automated approach to identify potentially nocuous ambiguity, which occurs when text is interpreted differently by different readers. We concentrate on anaphoric ambiguity, which occurs when readers may disagree on how pronouns should be interpreted. We describe a number of heuristics, each of which captures information that may lead a reader to favor a particular interpretation of the text. We use these heuristics to build a classifier, which in turn predicts the degree to which particular interpretations are preferred. We collected multiple human judgements on the interpretation of requirements exhibiting anaphoric ambiguity and showed how the distribution of these judgements can be used to assess whether a particular instance of ambiguity is nocuous. Given a requirements document written in natural language, our approach can identify sentences that contain anaphoric ambiguity, and use the classifier to alert the requirements writer of text that runs the risk of misinterpretation. We report on a series of experiments that we conducted to evaluate the performance of the automated system we developed to support our approach. The results show that the system achieves high recall with a consistent improvement on baseline precision subject to some ambiguity tolerance levels, allowing us to explore and highlight realistic and potentially problematic ambiguities in actual requirements documents.     

A framework to integrate design knowledge reuse and requirements management in engineering design

This paper presents a framework to integrate requirements management and design knowledge reuse. The research approach begins with a literature review in design reuse and requirements management to identify appropriate methods within each domain. A framework is proposed based on the identified requirements. The framework is then demonstrated using a case study example: vacuum pump design. Requirements are presented as a component of the integrated design knowledge framework. The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements. It takes account of the evolving requirements and the dynamic nature of the interaction between requirements and product structure through the various stages of product development.