Specification Text Research Articles

A Non-Exclusive Multi-Class Convolutional Neural Network for the Classification of Functional Requirements in AUTOSAR Software Requirement Specification Text

Software Requirement Specification (SRS) describes a software system to be developed that captures the functional, non-functional, and technical aspects of the stakeholder’s requirements. Retrieval and extraction of software information from SRS are essential to the development of software product line (SPL). Albeit Natural Language Processing (NLP) techniques, such as information retrieval and standard machine learning, have been advocated in the recent past as a semi-automatic means of optimising requirements specifications, they have not been widely embraced. The complexity in the organization’s information makes requirement analysis intricately a challenging task. The interdependence of subsystems and within an organisation drives this complexity. A plain multi-class classification framework may not address this issue. Hence, this paper propounds an automated non-exclusive approach for classification of functional requirements from SRS, using a deep learning framework. Specifically, Word2Vec and FastText word embeddings are utilised for document representation for training a convolutional neural network (CNN). The study was carried out by the compilation of manually categorised relevant enterprise data (AUTomotive Open System ARchitecture (AUTOSAR)), which were also employed for model training. Over a convolutional neural network, the impact of data trained with Word2Vec and FastText word embeddings from SRS documentation were compared to pre-trained word embeddings models, available online.

Internet User Consumption Behavior Based on Big Data

With the vigorous development of the Internet economy, competition in the domestic market has become increasingly fierce. This research mainly discusses the consumption behavior of Internet users based on big data. Text preprocessing is required first after the target text has been obtained. Clean and delete content that is of no value or limited value in the text. First, define the Request network connection request. Secondly, write a function module for obtaining multiple commodity IDs. Traverse the full text to obtain the target content, which is often used to retrieve and replace the target text. Finally, the crawling of individual product information. According to the research product goals, big data technology is used to obtain data on two dimensions of product sales information and user experience information. Store the product sales specification text and product review text as divergent texts for the next stage of data cleaning to predict user consumption behavior. The function of the product, in the price range of 100-200 yuan, the user’s attention is 27%. This research helps companies formulate precise marketing strategies.

Verification of the European Rail Traffic Management System in Real-Time Maude

The European Rail Traffic Management System (ERTMS) is a state-of-the-art train control system designed as a standard for railways across Europe. It generalises traditional discrete interlocking systems to a world in which trains hold on-board equipment for signalling, and trains and interlockings communicate via radio block processors. The ERTMS aims at improving performance and capacity of rail traffic systems without compromising their safety. The ERTMS system is of hybrid nature, in contrast to classical railway signalling systems which deal with discrete data only. Consequently, the switch to ERTMS poses a number of research questions to the formal methods community, most prominently: How can safety be guaranteed? In this paper we present the first formal modelling of ERTMS comprising all subsystems participating in its control cycle. We capture what safety means in physical and in logical terms, and we demonstrate that it is feasible to prove safety of ERTMS systems utilising Real-Time Maude model-checking by considering a number of bi-directional track layouts. ERTMS is currently being installed in many countries. It will be the main train control standard for the foreseeable future. The concepts presented in this paper offer applicable methods supporting the design of dependable ERTMS systems. We demonstrate model-checking to be a viable option in the analysis of large and complex real-time systems. Furthermore, we establish Real-Time Maude as a modelling and verification tool applicable to the railway domain. The approach given in this paper is a rigorous one. In order to avoid modelling errors, we follow a systematic approach: First, as a requirement specification, we identify the event-response structures present in the ERTMS. Then, we model these structures in Real-Time Maude in a traceable way, i.e., specification text in Real-Time Maude can be directly mapped to requirements. We explore our models by checking if they have the desired behaviour, and apply systematic model-exploration through error injection – both these steps are carried out using the formal method Real-Time Maude. Finally, we analyse ERTMS by model-checking, thus applying a formal method to the railway domain, and we mathematically prove that our analysis of ERTMS by model-checking is complete, i.e., that it guarantees safety at all times. • First full model of ERTMS, i.e., comprising all subsystems required for the full control cycle. • Systematic modelling, validation, and verification process on ERTMS. • Completeness argument for the verification of a hybrid system through finitely many time samples. • Modelling technique for time-robustness and tick-stability in case of numerical rounding errors. • Successful application of Real-Time Maude to a new industrially relevant domain.

Automatic Domain Knowledge Extraction from Requirements Specification Text

The automated generation of sequence of actions and schema extraction from requirements specification text written in natural language is really challenging and has limited explorations so far. It’s an attempt to automatically retrieving some useful elements from the requirements specification text, which is required for the software development process. This study proposes a system to simplify requirements analysis process and identify the interaction between the class objects using Natural Language Processing (NLP) techniques and crafted rules. The Automatic Domain Knowledge Extraction (ADKE) system does the step by step elicitation of classes, attributes, relationships, actors, relational schema, use cases and interaction between the classes. Finally deploys relational schema into the database, which allows user to acquire domain knowledge by applying queries and quick traceability link between the use cases. The experimental results of ADKE system are compared with other available tools and it gives better accuracy also.

The PENG ASP system: architecture, language and authoring tool

In this article, we describe the architecture, the language and the authoring tool of the PENG$$^{ASP}$$ASP system. This system supports the writing of non-monotonic specifications in controlled natural language with the help of a web-based predictive text editor. This predictive editor communicates asynchronously with a controlled natural language processor that translates the specification text via discourse representation structures into executable Answer Set Programs (ASP). The controlled natural language processor additionally generates lookahead categories and anaphoric expressions for the author of a specification text, and it provides a paraphrase of the specification that clarifies the interpretation of the text by the machine. The predictive editor is a central component of the PENG$$^{ASP}$$ASP system; it guides the writing process and displays multiple sets of lookahead categories simultaneously for different possible sentence completions as well as anaphoric expressions, and supports the addition of new content words to the lexicon .

Metrics for quantifying evolutionary changes in Z specifications

SUMMARYThis article proposes metrics for quantifying changes throughout the evolution of formal software specifications in long living systems. Formal specifications play an important role in the software development life‐cycle by supporting refinement and proof and by providing a basis for comprehension and maintenance activities. However, specifications also undergo evolutionary changes, and these changes are hard to assess because of a lack of suitable measures.This paper proposes and analyzes a set of measures for estimating aspects of a specification's complexity and quality. The measures are based on existing measures for source code, but they have been redefined in the scope of formal Z specifications. Geared towards Z, they are then evaluated concerning their expressiveness by a case study that comprises more than 65,000 lines of specification text. Finally, the usability of the measures is demonstrated on the Z specification of the Web Service Definition Language during its evolution over a period of about 3 years. Copyright © 2013 John Wiley & Sons, Ltd.

Prediction of modulators of pyruvate kinase in smiles text using aprori methods

Pyruvate kinase is an enzyme that catalyzes the formation of pyruvate from phosphenolpyruvate in glycolysis. There is a wealth of data on the activity of certain molecules and their effects on pyruvate kinase. This project aims to create an application that uses a pyruvate kinase dataset to determine the nature of unidentified molecules; whether or not they would be activators or inhibitors of this enzyme. This application uses an Apriori algorithm to identify or predict modulators of pyruvate kinase. This initial study focuses on simplified molecular input line entry specification (SMILES) text as target data to be mined. The three dimensional structure of pyruvate kinase is known and accessible though the Protein Data Bank (e.g., PDB code IA3W).

Rhetorical Invention in Design

Though scholars have begun to explore how texts mediate design, little is known about rhetorical invention in design. To investigate how heuristics used for rhetorical invention and design might be related, the author analyzed how one disciplinary design heuristic, the information system cliché, influenced the production of both a computer system and a specification text for the system. The cliché was used to generate design proposals, which designers evaluated using at least three criteria: projected context of use, correspondence between the proposals and their textual inscriptions, and system coherence. Results indicate that disciplinary heuristics and rhetorical topics overlap in design; however, the rhetorical character of disciplinary heuristics is obscured in textual representations of the design. Both types of heuristic serve as interpretive instruments and are used dialogically to develop the parts of a design or text within the context of the whole.

Preparing specifications by computer

A marked increase in accuracy and efficiency has been achieved by the US Army Corps of Engineers with a computerised system for preparing specifications for its construction projects. Known as ‘Editspec’, the system simplifies the selection of design conditions taken from master guides, allows for updating or specification changes and finally automatically prints out the correct specification text for the complete project. Its operation is explained here by a member of the US Construction Egineering Research Laboratory, which devised the system.