Skill UI

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.

This guide outlines the mandatory open data and code requirements for publishing in Global Change Biology (GCB). It details that primary and secondary data, along with supporting code/software, must be archived in public, DOI-minting repositories (e.g., Dryad, Zenodo) prior to acceptance. It emphasizes that 'available on request' is not accepted and provides a structured checklist for ensuring reproducibility and proper metadata submission.

This guide provides comprehensive standards for designing, executing, and reporting systems experiments for top-tier academic venues (like ICDE). It emphasizes methodological rigor, including mandatory ablation studies, reporting variance and tail latency (p99), demonstrating scaling trends (curves over points), disclosing cost trade-offs, and ensuring full hardware and software reproducibility to withstand adversarial review.

This guide outlines comprehensive standards for scientific reproducibility in data engineering. It details best practices for pinning hardware, software, datasets, and variance protocols, ensuring that all performance claims are verifiable and re-runnable by peers, making reproducibility a scored component of academic submission.

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 guide provides comprehensive best practices for authors submitting software artifacts to academic venues like ICSME. It details how to structure packages, track provenance, and document code to achieve the IEEE Open Research Object and Research Object Reviewed badges. Learn how to design for rigorous, reproducible evaluation by evaluators in a bounded time frame.

A comprehensive methodology guide for designing and auditing empirical studies in software engineering, specifically focused on maintenance, evolution, and change impact. It outlines best practices for ensuring evidence is proportional to the claim, managing data provenance (SHAs, criteria), handling statistical confounds (survivorship, effect sizes), and integrating rigorous LLM evaluation protocols.

A comprehensive guide for auditing and positioning the novelty and eligibility of research submissions in the field of software maintenance and evolution. It teaches authors to write a 'delta-first' related work section, contrasting their contribution against key prior works and covering specialized literature lanes (e.g., MSR, ICSE, TSE) to demonstrate deep command of the academic 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.