Automated Software Tool Support for Checking the Inconsistency of Requirements

Handling inconsistency in software requirements is a complicated task which has attracted the interest of many groups of researchers. Formal and semi-formal specifications often have inconsistencies in the depicted requirements that need to be managed and resolved. This is particularly challenging when refining informal to formalized requirements. We propose an automated tool with traceability and consistency checking techniques to support analysis of requirements and traceability between different representations: textual, visual, informal and formal

MEReq: A Tool to Capture and Validate Multi-Lingual Requirements

Within the era of globalisation that acknowledges differences and diversity, multiple languages have been increasingly used to capture requirements. This practice is particularly prevalent in Malaysia, where both Malay and English languages are used as a media of communication. Nevertheless, capturing requirements in multiple languages is often error-prone due to natural language imprecision being compounded by language differences. Considering that two languages may be used to describe requirements for the same system in different ways, we were motivated to develop MEReq, a tool which uses Essential Use Case (EUC) models to support capturing and checking the inconsistency occurring in English and Malay multi-lingual requirements. MEReq is tablet compatible to minimise time for on-site capture and validation of multi-lingual requirements. This paper describes the MEReq approach and demonstrates its use to capture and validate English and Malay requirements

Improving Requirements Completeness: Automated Assistance through Large Language Models

Natural language (NL) is arguably the most prevalent medium for expressing systems and software requirements. Detecting incompleteness in NL requirements is a major challenge. One approach to identify incompleteness is to compare requirements with external sources. Given the rise of large language models (LLMs), an interesting question arises: Are LLMs useful external sources of knowledge for detecting potential incompleteness in NL requirements? This article explores this question by utilizing BERT. Specifically, we employ BERT's masked language model (MLM) to generate contextualized predictions for filling masked slots in requirements. To simulate incompleteness, we withhold content from the requirements and assess BERT's ability to predict terminology that is present in the withheld content but absent in the disclosed content. BERT can produce multiple predictions per mask. Our first contribution is determining the optimal number of predictions per mask, striking a balance between effectively identifying omissions in requirements and mitigating noise present in the predictions. Our second contribution involves designing a machine learning-based filter to post-process BERT's predictions and further reduce noise. We conduct an empirical evaluation using 40 requirements specifications from the PURE dataset. Our findings indicate that: (1) BERT's predictions effectively highlight terminology that is missing from requirements, (2) BERT outperforms simpler baselines in identifying relevant yet missing terminology, and (3) our filter significantly reduces noise in the predictions, enhancing BERT's effectiveness as a tool for completeness checking of requirements.Comment: Submitted to Requirements Engineering Journal (REJ) - REFSQ'23 Special Issue. arXiv admin note: substantial text overlap with arXiv:2302.0479

Specification Patterns for Robotic Missions

Mobile and general-purpose robots increasingly support our everyday life, requiring dependable robotics control software. Creating such software mainly amounts to implementing their complex behaviors known as missions. Recognizing the need, a large number of domain-specific specification languages has been proposed. These, in addition to traditional logical languages, allow the use of formally specified missions for synthesis, verification, simulation, or guiding the implementation. For instance, the logical language LTL is commonly used by experts to specify missions, as an input for planners, which synthesize the behavior a robot should have. Unfortunately, domain-specific languages are usually tied to specific robot models, while logical languages such as LTL are difficult to use by non-experts. We present a catalog of 22 mission specification patterns for mobile robots, together with tooling for instantiating, composing, and compiling the patterns to create mission specifications. The patterns provide solutions for recurrent specification problems, each of which detailing the usage intent, known uses, relationships to other patterns, and---most importantly---a template mission specification in temporal logic. Our tooling produces specifications expressed in the LTL and CTL temporal logics to be used by planners, simulators, or model checkers. The patterns originate from 245 realistic textual mission requirements extracted from the robotics literature, and they are evaluated upon a total of 441 real-world mission requirements and 1251 mission specifications. Five of these reflect scenarios we defined with two well-known industrial partners developing human-size robots. We validated our patterns' correctness with simulators and two real robots

Ontology-based methodology for error detection in software design

Improving the quality of a software design with the goal of producing a high quality software product continues to grow in importance due to the costs that result from poorly designed software. It is commonly accepted that multiple design views are required in order to clearly specify the required functionality of software. There is universal agreement as to the importance of identifying inconsistencies early in the software design process, but the challenge is how to reconcile the representations of the diverse views to ensure consistency. To address the problem of inconsistencies that occur across multiple design views, this research introduces the Methodology for Objects to Agents (MOA). MOA utilizes a new ontology, the Ontology for Software Specification and Design (OSSD), as a common information model to integrate specification knowledge and design knowledge in order to facilitate the interoperability of formal requirements modeling tools and design tools, with the end goal of detecting inconsistency errors in a design. The methodology, which transforms designs represented using the Unified Modeling Language (UML) into representations written in formal agent-oriented modeling languages, integrates object-oriented concepts and agent-oriented concepts in order to take advantage of the benefits that both approaches can provide. The OSSD model is a hierarchical decomposition of software development concepts, including ontological constructs of objects, attributes, behavior, relations, states, transitions, goals, constraints, and plans. The methodology includes a consistency checking process that defines a consistency framework and an Inter-View Inconsistency Detection technique. MOA enhances software design quality by integrating multiple software design views, integrating object-oriented and agent-oriented concepts, and defining an error detection method that associates rules with ontological properties

A New Consistency Validation Approach to Enhance the Quality of Functional Security Requirements for Secure Software

Quality security requirements contribute to the success of secure software development. However, the process of eliciting security requirements is tedious and complex. It also requires requirements engineers to have security experience in the process of eliciting consistent security requirements from the clients-stakeholders. Most of the requirements engineers faced problems in eliciting consistent security compliance requirements from the clients-stakeholders as they misunderstood the real needs and the security term used. Thus, this resulted to inconsistent security requirements being elicited. The inconsistency leads to incorrect and insecure software systems being developed as well as to disruptions of schedule and increase of a project's expenditure. Motivated by these problems, this study is aimed to propose a new approach for consistency validation of functional security requirements. Here, security requirements specifications will be collected from software vendors to analyse the flow of functional security requirements process. Next, visual differencing will be integrated to cross-validate the consistency of the elicited functional security requirements with the best-practise template. Here, security requirements best-practice template pattern library will be designed and a new mathematical formulation that defines the consistency validation rules of security requirements will also be constructed. The formulation will be based on the security-related semi-formalised model, called SecEssential Use Case (SecEUC).This approach will then be realised with a proof of concept prototype tool and will be compared with the existing approaches, focusing on its ability to validate the inconsistency of the functional security requirements. Finally, this study is believed could provide a positive impact to the software industry by reducing the development cost as it allows the requirements engineers to validate the inconsistency that occurs in the elicited security compliance requirements at the early stage of the secure software development

Systematic literature review of domain-oriented specification techniques

Context: The popularity of domain-specific languages and model driven development has made the tacit use of domain knowledge in system development more tangible. Our vision is a development process where a (software) system specification is based on multiple domain models, and where the specification method is built from cognitive concepts, presumably derived from natural language. Goal: To realize this vision, we evaluate and reflect upon the existing literature in domain-oriented specification techniques. Method: We designed and conducted a systematic literature review on domain-oriented specification techniques. Results: We identified 53 primary studies, populated the classification framework for each study, and summarized our findings per classification aspect. We found many approaches for creating domain models or domain-specific languages. Observations include: (i) most methods are defined incompletely; (ii) none offers methodical support for the use of domain models or domain-specific languages to create other specifications; (iii) there are specification techniques to integrate models in general, but no study offers methodical support for multiple domain models. Conclusion: The results indicate which topics need further research and which can instead be reused to realize our vision on system development. Editor\u27s note: Open Science material was validated by the Journal of Systems and Software Open Science Board