Olga Ormandjieva

Automatic transition of natural language software requirements specification into formal presentation

Software requirements specification is a critical activity of the software process, as errors at this stage inevitably lead to problems later on in system design and implementation. The requirements are written in natural language, with the potential for ambiguity, contradiction or misunderstanding, or simply an inability of developers to deal with a large amount of information. This paper proposes a methodology for the natural language processing of textual descriptions of the requirements of an unlimited natural language and their automatic mapping to the object-oriented analysis model.

An Ontology Based Approach to Non-functional Requirements Conceptualization

The growing awareness of the importance of Non- Functional Requirements (NFRs) among the requirements engineering (RE) community in the last few years led to a heightened interest in NFRs description and modeling and, in turn, to the emergence of several models intended to capture and structure the relevant concepts defining the NFRs and their relations. Yet, most of the terms and concepts in use for describing NFRs have been loosely defined, and often there is no commonly accepted taxonomy of NFRs. Common Foundation is required to enable effective communication and to enable integration of NFRs’ related research activities within the RE community. In this paper, this Common Foundation will be realized by developing an ontology-based approach which is adequate for projects taking into consideration the NFRs and their relations earlier in the software development and throughout the life cycle.

Toward a text classification system for the quality assessment of software requirements written in natural language

Requirements Engineering (RE) is concerned with the gathering, analyzing, specifying and validating of user requirements that are documented mostly in natural language. The artifact produced by the RE process is the software requirements specification (SRS) document. The success of a software project largely depends on the quality of SRS documentation, which serves as an input to the design, coding and testing phases. This paper approaches the problem of the automatic quality assessment of textual requirements from an innovative point of view, namely the use of the Natural Language Processing (NLP) text classification technique. The paper proposes a quality model for the requirements text and a text classification system to automate the quality assessment process. A large study evaluating the discriminatory power of the quality characteristics and the feasibility of a tool for the automatic detection of ambiguities in requirements documentation is presented. The study also provides a benchmark for such an evaluation and an upper bound on what we can expect automatic requirements quality assessment tools to achieve. The reported research is part of a larger project on the applicability of NLP techniques to assess the quality of artifacts produced in RE.

Models Derived from Automatically Analyzed Textual User Requirements

Requirements engineering is an important area of software engineering concerned with the extraction and presentation of knowledge from user requirements. There is a considerable gap between the various types of presentation of the same kinds of knowledge - those of the user written in natural language (NL) and those of requirements engineering (RE) depicted using diagrams (de facto standard UML diagrams, for example). Our research is aimed at filling that gap. In this paper, we introduce a universal formalism based on the basic building unit of NL, which is the relation triad. Through the definition of these basic relations in NL, we create three RE models: the use case path model, the hybrid activity diagram model and the domain model. These models are abstractions of the knowledge contained in the text, and serve as the basis for deriving UML diagrams

Using Linguistic Knowledge to Classify Non-functional Requirements in SRS documents

Non-functional Requirements (NFRs) such as software quality attributes, software design constraints and software interface requirements hold crucial information about the constraints on the software system under development and its behavior. NFRs are subjective in nature and have a broad impact on the system as a whole. Being distinct from Functional Requirements (FR), NFRs are dealt with special attention, as they play an integral role during software modeling and development. However, since Software Requirements Specification (SRS) documents, in practice, are written in natural language, solely holding the perspectives of the clients, the documents often end up with FR and NFR statements mixed together in the same paragraphs. It is, therefore, left upon the software analysts to classify and separate them manually. The research, presented in this paper, aims to automate the process of detecting NFR sentences by using a text classifier equipped with a part-of-speech (POS) tagger. The results reported in this paper outperform the recent work in the field, and achieved a higher accuracy of 98.56% using 10-folds-cross-validation over the same data used in the literature. The research reported in this paper is part of a larger project aimed at applying Natural Language Processing techniques in Software Requirements Engineering.

Approximation of COSMIC functional size to support early effort estimation in Agile

The demands in the software industry of estimating development effort in the early phases of development are met by measuring software size from user requirements. A large number of companies have adapted themselves with Agile processes, which, although, promise rapid software development, pose a huge burden on the development teams for continual decision making and expert judgement, when estimating the size of the software components to be developed at each iteration. COSMIC, on the other hand, is an ISO/IEC international standard that presents an objective method of measuring the functional size of the software from user requirements. However, its measurement process is not compatible with Agile processes, as COSMIC requires user requirements to be formalised and decomposed at a level of granularity where external interactions with the system are visible to the human measurer. This time-consuming task is avoided by agile processes, leaving it with the only option of quick subjective judgement by human measurers for size measurement that often tends to be erroneous. In this article, we address these issues by presenting an approach to approximate COSMIC functional size from informally written textual requirements demonstrating its applicability in popular agile processes. We also discuss the results of a preliminary experiment studying the feasibility of automating our approach using supervised text mining.

Automated generation of test suites from formal specifications of real-time reactive systems

Real-time reactive systems are among the most difficult systems to test because of their size and complex time-dependent functionality. The number of test experiments for such systems is very large, if not infinite. Often such systems arise in safety-critical contexts. Hence, such systems require a rigorous analysis and thorough testing before they are deployed. This paper addresses test case generation methods and a metric-based test case selection algorithm for sufficient testing of real-time reactive systems. The methods are rigorous, and based on the formal specifications of the system and its fault models. The test generation and execution of algorithms are implemented in TROMLAB, a formal framework for developing real-time reactive systems. The methods are applied to the formal specification of the Train-Gate-Controller (TGC) example, a bench-mark case study in the real-time systems community. A brief description of the experimental results obtained on the case study is given.

Ontology-Based Classification of Non-functional Requirements in Software Specifications: A New Corpus and SVM-Based Classifier

A software requirements specification (SRS) contains all the requirements for a system-to-be. These are typically separated into functional requirements (FR), which describe the features of the system under development, and the non-functional requirements (NFR), which include quality attributes, design constraints, among others. It is well known that NFRs have a large impact on the overall cost and time of the system development process, as they frequently describe cross-cutting concerns. In order to improve software development support, an automated analysis of SRS documents for different NFR types is required. Our work contains two significant contributions towards this goal: (1) A new gold standard corpus containing annotations for different NFR types, based on a requirements ontology, and (2) a Support Vector Machine (SVM) classifier to automatically categorize requirements sentences into different ontology classes. Results obtained from two different SRS corpora demonstrate the effectiveness of our approach.

Characterising Context for Mobile User Interfaces in Health Care Applications

Mobile technology has been piloted in a variety of domains. We investigate the use of smart phones in the hospital environment, as they can play an important role in the recording and exchanging of information. This paper examines how context can be characterised for developing context sensitive user interfaces for smart phone application in a hospital environment. We introduce a new characterisation of the notion of context, based on the principle of separation of the concerns that are relevant to the application domain. We coin the term context descriptor, which captures the notion of context at the end-user level, while the characterisation of the context incorporates the user model via the user stereotype. We use a sub-domain of health care, nursing services, the tasks of the nurses serving as a living example to illustrate the ideas presented.

A New Quality-in-Use Model for Mobile User Interfaces

This paper proposes a new quality-in-use model for measuring user interface design quality, and is intended specifically for mobile devices. The proposed model is based on the international standard ISO 9126-4 [ISO/IEC TR 9126-4:2004] and can be adapted to various applications. The quality-in-use factors of effectiveness, productivity, efficiency, safety, and satisfaction are redefined to reflect the ways in which mobile devices are used, and the contexts in which they are used. A new factor, task navigation, is proposed to measure the cognitive load on the user when he or she interacting with the interface across different platforms. Our objectives include theoretical and empirical validation of the proposed measurement model.