English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

High quality software systems typically require a set of clear, complete andcomprehensive requirements. In the process of software development life cycle,a software requirement specification (SRS) document lays the foundation ofproduct development by defining the set of functional and nonfunctionalrequirements. It also improves the quality of software products and ensuretimely delivery of the projects. These requirements are typically documented innatural language which might lead to misinterpretations and conflicts betweenthe requirements. In this study, we aim to identify the conflicts inrequirements by analyzing their semantic compositions and contextual meanings.We propose an approach for automatic conflict detection, which consists of twophases: identifying conflict candidates based on textual similarity, and usingsemantic analysis to filter the conflicts. The similarity-based conflictdetection strategy involves finding the appropriate candidate requirements withthe help of sentence embeddings and cosine similarity measures. Semanticconflict detection is an additional step applied over all the candidatesidentified in the first phase, where the useful information is extracted in theform of entities to be used for determining the overlapping portions of textsbetween the requirements. We test the generalizability of our approach usingfive SRS documents from different domains. Our experiments show that theproposed conflict detection strategy can capture the conflicts with highaccuracy, and help automate the entire conflict detection process.

Identifying the requirement conflicts in SRS documents using transformer-based sentence embeddings