CORG: a Component-oriented synthetic textual requirements generator

Aya Zaki-Ismail, Mohamed Osama, Mohamed Abdelrazek, John Grundy, Amani Ibrahim

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review


The majority of requirements formalisation techniques operate on textual requirements as input. To establish and verify the reliability and coverage of such techniques, a large set of textual requirements with diverse structures and formats is required. However, such techniques are typically evaluated on only a few manually curated requirements that do not provide enough coverage of the targeted structures. Motivated by this problem, we introduce a Component-oriented synthetic textual requirements generator (CORG) that can generate large numbers of synthesised diverse-structure textual requirements, along with key components breakdowns. CORG utilises a controlled random-selection (CRS) strategy throughout the backtracking-based generation. We evaluate the coverage, diversity, performance and correctness of CORG. The evaluation results show that CORG can generate comprehensive diverse-structure combinations in reasonable time without being affected by the size of the produced requirements.

Original languageEnglish
Title of host publication27th International Working Conference, REFSQ 2021 Essen, Germany, April 12–15, 2021 Proceedings
EditorsFabiano Dalpiaz, Paola Spoletini
Place of PublicationCham Switzerland
Number of pages17
ISBN (Electronic)9783030731281
ISBN (Print)9783030731274
Publication statusPublished - 2021
EventInternational Workshop on Requirements Engineering: Foundation for Software Quality 2021 - Online, Germany
Duration: 12 Apr 202115 Apr 2021
Conference number: 27th (Proceedings)

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceInternational Workshop on Requirements Engineering: Foundation for Software Quality 2021
Abbreviated titleREFSQ 2021
Internet address


  • Requirements engineering
  • Text generation

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