Skill UI

A comprehensive guide for researchers submitting to ASE (Automated Software Engineering). It details mandatory requirements for ensuring research reproducibility, covering the Data Availability Statement, providing anonymized and runnable tools, pinning system provenance (commits, versions, SHAs), and managing cached LLM outputs. Essential for passing rigorous peer review.

This guide provides a rigorous framework for designing and auditing empirical studies in software engineering (SE). It emphasizes that evidence must proportionally match the claims made, covering topics like using real subject systems, establishing fair baselines, calculating SE-standard statistics (effect sizes, CIs), and ensuring thorough provenance, especially for LLM-based work. It helps researchers strengthen their research methodology before publication.

A comprehensive guide for revising empirical papers submitted to top-tier Software Engineering conferences (like FSE). This framework emphasizes structuring the paper around a clear SE contribution, treating research questions as contracts, backing every claim with proportional evidence, and rigorously arguing threats to validity, rather than merely listing them. It ensures the paper maintains maximum academic rigor and focus.

A comprehensive guide for designing, executing, and reporting high-stakes research studies in Software Engineering (SE), tailored to meet the stringent standards of top academic conferences like ICSE. It covers best practices for evidence-claim matching, advanced statistical rigor (non-parametric tests, effect sizes), handling AI model ablations, and implementing threats-driven design to ensure findings are robust, valid, and maximally reproducible.

A detailed methodology guide for authors submitting to highly competitive software engineering venues (like ICSE). It teaches how to structure the Related Work section not as a bibliography, but as a 'delta statement' that explicitly outlines the unique differences and contributions compared to the state-of-the-art across multiple publication lanes (journals, preprints, flagship venues).

This guide helps software engineering researchers determine the most appropriate academic conference or journal venue for their work. It provides comprehensive fit tests based on contribution type, empirical evidence maturity, and potential impact on industry practice. Authors learn to evaluate their research against criteria like novelty, rigor, and real-world relevance, ensuring proper routing to specialized tracks (e.g., ISSTA, ASE, ICSE).

This guide provides detailed structuring advice for writing empirical software engineering (SE) research papers for top-tier conferences like ICSE. It focuses on adopting the required academic rigor, including using Research Questions (RQs) as the core skeleton, mastering the 'Threats to Validity' section, and calibrating claims for verifiability. Learn how to structure the abstract, compress content into a 10-page limit, and address reviewer expectations in the SE community.

This comprehensive guide assists software engineers in determining the most appropriate venue (e.g., ICSME, ICSE, MSR) for their research paper. It clarifies the critical difference between general software engineering techniques and studies focused on the post-release lifecycle, such as maintenance, technical debt, program comprehension, and system evolution.

A comprehensive tool designed to help authors assess the suitability and optimal framing of their manuscripts for the IEEE/ACM International Conference on Automated Software Engineering (ASE). It guides the structuring of contributions, required evidence (runnable artifacts, benchmarks), and positioning relative to core SE concepts like program analysis, testing, and AI-assisted development. Use this guide to strategize conference submissions and strengthen the academic narrative.

A comprehensive guide for authors targeting the IEEE International Conference on Data Engineering (ICDE). This skill helps assess venue fit, re-frame manuscripts from journal/arXiv styles, and structure papers for top CS conferences. It details required evidence (system architecture, realistic workloads) and best practices for positioning contributions in data engineering, database systems, and analytics.

This guide assists authors with positioning their computer science manuscripts for the IEEE International Conference on Software Maintenance and Evolution (ICSME). It details the core scope, including software maintenance, evolution, refactoring, and technical debt, and provides best practices for structuring submissions. It emphasizes the need for real repository evidence, actionable engineering insights, and proper differentiation from related venues like SANER or ICSE.

This guide provides comprehensive guidelines for designing, conducting, and auditing empirical studies in software engineering. It emphasizes achieving scientific rigor by matching every claim to specific, measured evidence, ensuring fair baselining (equal budget), and applying appropriate advanced statistics (non-parametric tests, effect sizes). Essential reading for researchers submitting papers based on performance evaluations.