Subtopic Deep Dive
Requirements Engineering in Software Projects
Research Guide
What is Requirements Engineering in Software Projects?
Requirements Engineering in Software Projects encompasses processes for eliciting, analyzing, specifying, validating, and managing software requirements to align systems with stakeholder needs.
This subtopic covers elicitation techniques, traceability, volatility management, and user involvement strategies, often tested via controlled experiments. Key works include Nuseibeh and Easterbrook (2000, 1792 citations) providing a comprehensive roadmap and Kotonya and Sommerville (1998, 1710 citations) detailing processes and techniques. Over 10 highly cited papers from 1988-2009 address non-functional requirements and empirical methods.
Why It Matters
Poor requirements cause 70% of software project failures, leading to rework costs exceeding 40% of budgets (Curtis et al., 1988). Improved RE practices reduce defects and enhance project success, as shown in field studies of large systems where fluctuating requirements amplified design issues (Curtis et al., 1988). Chung and Leite (2009) highlight non-functional requirements' role in system quality, while Nuseibeh and Easterbrook (2000) link effective RE to better stakeholder alignment in complex projects.
Key Research Challenges
Requirements Volatility Management
Fluctuating requirements disrupt large projects, thinning application domain knowledge spread (Curtis et al., 1988). Managing changes requires traceability tools and processes (Nuseibeh and Easterbrook, 2000). Empirical studies show volatility correlates with design rework (Curtis et al., 1988).
Non-Functional Requirements Elicitation
Non-functional requirements like performance and security are harder to specify than functional ones (Chung and Leite, 2009). Frameworks for modeling them exist but lack integration with functional specs (Chung et al., 2000). Validation remains inconsistent in positivist research (Straub and Gefen, 2004).
Empirical Validation of RE Methods
Controlled experiments testing RE efficacy on outcomes are scarce due to methodological rigor needs (Runeson and Höst, 2008). Systematic mapping identifies gaps in publication frequencies (Petersen et al., 2008). Positivist validation guidelines stress instrument reliability (Straub and Gefen, 2004).
Essential Papers
Guidelines for conducting and reporting case study research in software engineering
Per Runeson, Martin Höst · 2008 · Empirical Software Engineering · 3.7K citations
Systematic Mapping Studies in Software Engineering
Kai Petersen, Robert Feldt, Shahid Mujtaba et al. · 2008 · Electronic workshops in computing · 3.0K citations
BACKGROUND: A software engineering systematic map is a defined method to build a classification scheme and structure a software engineering field of interest. The analysis of results focuses on fre...
Validation Guidelines for IS Positivist Research
Detmar W. Straub, David Gefen · 2004 · Communications of the Association for Information Systems · 2.7K citations
The issue of whether IS positivist researchers were sufficiently validating their instruments was initially raised fifteen years ago and rigor in IS research is still one of the most critical scien...
On Non-Functional Requirements in Software Engineering
Lawrence Chung, Julio César Sampaio do Prado Leite · 2009 · Lecture notes in computer science · 2.2K citations
A field study of the software design process for large systems
Bill Curtis, Herb Krasner, Neil Iscoe · 1988 · Communications of the ACM · 2.1K citations
The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three of these problems—the th...
The Delphi Method for Graduate Research
Gregory James Skulmoski, Francis T. Hartman, Jennifer R Krahn · 2007 · Journal of Information Technology Education Research · 1.8K citations
The Delphi method is an attractive method for graduate students completing masters and PhD level research. It is a flexible research technique that has been successfully used in our program at the ...
Requirements engineering
Bashar Nuseibeh, Steve Easterbrook · 2000 · 1.8K citations
Article Free Access Share on Requirements engineering: a roadmap Authors: Bashar Nuseibeh Department of Computing, Imperial College, 180 Queen's Gate, London SW7 2BZ, U.K. Department of Computing, ...
Reading Guide
Foundational Papers
Start with Nuseibeh and Easterbrook (2000) for RE roadmap, Kotonya and Sommerville (1998) for processes, and Curtis et al. (1988) for field insights on large-system challenges.
Recent Advances
Prioritize Chung and Leite (2009) on non-functionals, Runeson and Höst (2008) for case study methods, and Petersen et al. (2008) for mapping RE literature.
Core Methods
Core techniques: systematic mapping (Petersen et al., 2008), case studies (Runeson and Höst, 2008), Delphi for elicitation (Skulmoski et al., 2007), and positivist validation (Straub and Gefen, 2004).
How PapersFlow Helps You Research Requirements Engineering in Software Projects
Discover & Search
Research Agent uses searchPapers and exaSearch to find core RE papers like 'Requirements engineering' by Nuseibeh and Easterbrook (2000), then citationGraph reveals 1792 citing works on volatility, while findSimilarPapers uncovers related empirical studies from Runeson and Höst (2008).
Analyze & Verify
Analysis Agent applies readPaperContent to extract volatility models from Curtis et al. (1988), verifies claims via CoVe against 17-project field data, and runs PythonAnalysis with pandas to statistically compare citation impacts across RE papers, graded by GRADE for empirical strength.
Synthesize & Write
Synthesis Agent detects gaps in non-functional RE integration (Chung and Leite, 2009), flags contradictions between process models (Curtis et al., 1992), and Writing Agent uses latexEditText, latexSyncCitations for Nuseibeh (2000), plus latexCompile for reports and exportMermaid for RE process diagrams.
Use Cases
"Analyze citation trends in requirements volatility papers using Python."
Research Agent → searchPapers('requirements volatility') → Analysis Agent → runPythonAnalysis(pandas plot of citations from Curtis 1988 vs Nuseibeh 2000) → matplotlib trend graph output.
"Draft LaTeX section on non-functional requirements frameworks."
Research Agent → findSimilarPapers(Chung 2009) → Synthesis → gap detection → Writing Agent → latexEditText + latexSyncCitations(10 RE papers) → latexCompile → formatted PDF section.
"Find GitHub repos implementing RE traceability tools from papers."
Research Agent → citationGraph(Nuseibeh 2000) → Code Discovery → paperExtractUrls → paperFindGithubRepo → githubRepoInspect → list of 5 repos with traceability code examples.
Automated Workflows
Deep Research workflow conducts systematic reviews by searchPapers on RE methods (Petersen et al., 2008 style mapping), analyzing 50+ papers into structured reports with GRADE grading. DeepScan applies 7-step CoVe to validate claims in Curtis et al. (1988) field study. Theorizer generates theory on volatility impacts from Chung (2009) and Nuseibeh (2000) literature.
Frequently Asked Questions
What is Requirements Engineering?
Requirements Engineering defines processes for eliciting, specifying, validating, and managing software needs (Nuseibeh and Easterbrook, 2000; Kotonya and Sommerville, 1998).
What are key methods in RE?
Methods include case studies (Runeson and Höst, 2008), systematic mapping (Petersen et al., 2008), and non-functional modeling (Chung and Leite, 2009).
What are seminal RE papers?
Top papers: Nuseibeh and Easterbrook (2000, 1792 citations), Kotonya and Sommerville (1998, 1710 citations), Chung et al. (2000, 1677 citations).
What are open problems in RE?
Challenges persist in volatility management (Curtis et al., 1988), empirical validation (Straub and Gefen, 2004), and non-functional integration (Chung and Leite, 2009).
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