Glosariusz

Ważne terminy i koncepcje z rozwoju oprogramowania, zarządzania projektami i pokrewnych dziedzin

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Configuration file in the project root for environment-specific variables and sensitive data; typically not versioned.
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AI systems that plan and execute multi-step tasks using tools under defined permissions.
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Computer systems that perform tasks associated with human cognition such as classification, prediction and language understanding.
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Business Process Model and Notation standard for diagramming business workflows.
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Parallel line of development in a version-control repository.
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Structured kickoff clarifying goals, constraints, stakeholders and success criteria for a project.
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Formal customer or internal objection about quantity, quality, price or service deviations.
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Recorded snapshot of changes in a version-control history with message and author metadata.
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Structured comparison of alternative products, vendors or service approaches in a market.
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AI field that derives information from images or video, such as detecting or classifying materials.
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Numeric estimate of how certain a model is about a prediction or extracted field.
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Lightweight isolated runtime package that includes an application and its dependencies.
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Keeping software in a releasable state so approved versions can be deployed on demand.
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Practice where every change that passes automated checks is deployed to production automatically.
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Practice of frequently merging code and automatically building and testing each change.
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Comma-separated values file format for exchanging tabular data between systems.
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Self-service web application where customers access documents, status and selected master-data functions.
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User-interface colour scheme with dark backgrounds and light foreground text.
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Structured representation of entities, attributes and relationships stored by an application.
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Fitness of data for use, covering completeness, accuracy, consistency, timeliness and uniqueness.
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Versioned script that changes database schema in a controlled, repeatable way.
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Culture and tooling that integrate software development and IT operations for faster, safer delivery.
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Structured digital record of a product’s composition, origin and sustainability-relevant attributes.
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Digital representation of a physical asset, yard or process used for monitoring and simulation.
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Platform for packaging applications and dependencies into portable containers.
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Design process model with discover/define and develop/deliver phases for problem and solution exploration.
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Running AI inference on local devices near the data source instead of only in the cloud.
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Process modelling notation linking events and functions, often used in ERP-oriented analysis.
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Large body of work that is broken down into multiple user stories or tasks.
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Enterprise Resource Planning software integrating core business processes on shared master and transactional data.
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Reusable software foundation that provides structure and common components for applications.
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Design pattern where people review, correct or approve AI suggestions before critical actions.
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Networked sensors and devices that stream operational measurements into software systems.
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Laravel starter kit providing authentication, teams/profile scaffolding and related application boilerplate.
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Graph of entities and relations used to represent structured domain knowledge.
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PHP web application framework with expressive syntax for MVC applications and common enterprise features.
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Neural model trained on large text corpora to understand and generate natural language.
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Laravel library for building dynamic interfaces mainly in PHP without heavy custom JavaScript.
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Subset of AI where models learn patterns from historical data instead of being fully hand-coded.
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Relatively stable reference data such as customers, materials, sites and contracts used across transactions.
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Process gap where information is retyped or transferred manually between systems or paper and digital forms.
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Smallest product increment that delivers enough value to learn from real users.
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Practices for deploying, monitoring and maintaining machine-learning systems in production.
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Visual draft of screens used to validate layout and interaction before full implementation.
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Continuous observation of application health, performance and errors in running systems.
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Machine learning that jointly uses multiple data types such as text, images and tables.
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NLP task that locates and classifies entities such as names, dates, quantities and locations in text.
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AI techniques for understanding and extracting structure from human language text.
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Technology that converts text in images or PDFs into machine-readable characters.
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Splitting large result sets into pages for efficient listing in user interfaces and APIs.
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Automated sequence of build, test and deployment steps triggered by code changes.
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Data analysis that estimates likely future outcomes from historical patterns.
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Maintenance approach that predicts equipment risk to schedule service before failure.
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Analytics that recommends actions under constraints, beyond merely predicting outcomes.
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Technique that discovers and analyses real process flows from event logs.
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Ordered list of desired product work items managed by the product owner.
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Two-dimensional barcode that encodes data for fast scanning with phones or industrial scanners.
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Stored collection of versioned project files and history, usually hosted in Git.
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UI approach that adapts layouts to different screen sizes and devices.
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HTTP-based application interface using resource-oriented endpoints and standard methods.
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Architecture that retrieves relevant documents and conditions an LLM answer on those sources.
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Security model that grants permissions according to assigned roles rather than individuals alone.
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Agile framework that delivers work in time-boxed sprints with defined roles and ceremonies.
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Script that inserts initial or demo data into a database after migrations.
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Capability for users to complete tasks digitally without waiting for staff mediation.
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Combining multiple sensor signals to obtain a more reliable estimate than any single source.
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Fixed-length iteration in which a Scrum team commits to delivering a potentially shippable increment.
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Strategic review of strengths, weaknesses, opportunities and threats.
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Concrete unit of work required to implement a story or technical change.
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Isolating data and configuration so one customer or organisation cannot access another’s records.
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Open-source OCR engine commonly used in prototypes and document pipelines.
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Predicting future values of sequentially ordered measurements over time.
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Splitting text into tokens (words, subwords or characters) for NLP model processing.
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Event-level business records created by day-to-day operations such as orders, weighings and invoices.
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Short requirement statement describing a user need and the value of fulfilling it.
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Storing text embeddings in a searchable index for semantic similarity retrieval.
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Optimisation problem of assigning stops to vehicles under capacity and time constraints.
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System for tracking changes to source code and enabling collaboration over time.
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Human or camera-supported check of material quality and composition at intake.
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Weighted or capacity-aware vehicle routing variant used in constrained logistics planning.
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Operational list of vehicles or loads currently expected or present on the recycling yard.
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Family of real-time object detection models widely used in computer-vision pipelines.
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