Programming tool

Software development

Core activities

* Processes
* Requirements
* Design
* Engineering
* Construction
* Testing
* Debugging
* Deployment
* Maintenance

Paradigms and models

* Agile
* Cleanroom
* Incremental
* Prototyping
* Spiral
* V model
* Waterfall

Methodologies and frameworks

* ASD
* DevOps
* DAD
* DSDM
* FDD
* IID
* Kanban
* Lean SD
* LeSS
* MDD
* MSF
* PSP
* RAD
* RUP
* SAFe
* Scrum
* SEMAT
* TSP
* UP
* XP

Supporting disciplines

* Configuration management
* Documentation
* Software quality assurance (SQA)
* Project management
* User experience

Practices

* ATDD
* BDD
* CCO
* CI
* CD
* DDD
* PP
* SBE
* Stand-up
* TDD

Tools

* Compiler
* Debugger
* Profiler
* GUI designer
* Modeling
* IDE
* Build automation
* Release automation
* Infrastructure as code
* Testing

Standards and Bodies of Knowledge

* BABOK
* CMMI
* IEEE standards
* ISO 9001
* ISO/IEC standards
* PMBOK
* SWEBOK
* ITIL

Glossaries

* Artificial intelligence
* Computer science
* Electrical and electronics engineering

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A programming tool or software development tool is a computer program that software developers use to create, debug, maintain, or otherwise support other programs and applications. The term usually refers to relatively simple programs, that can be combined together to accomplish a task, much as one might use multiple hand tools to fix a physical object. The most basic tools are a source code editor and a compiler or interpreter, which are used ubiquitously and continuously. Other tools are used more or less depending on the language, development methodology, and individual engineer,often used for a discrete task, like a debugger or profiler. Tools may be discrete programs, executed separately – often from the command line – or may be parts of a single large program, called an integrated development environment (IDE). In many cases, particularly for simpler use, simple ad hoc techniques are used instead of a tool, such as print debugging instead of using a debugger, manual timing (of overall program or section of code) instead of a profiler, or tracking bugs in a text file or spreadsheet instead of a bug tracking system.

The distinction between tools and applications is murky. For example, developers use simple databases (such as a (Flat file database|file containing a list of important values]]) all the time as tools. However a full-blown database is usually thought of as an application or software in its own right. For many years, computer-assisted software engineering (CASE) tools were sought after. Successful tools have proven elusive. In one sense, CASE tools emphasized design and architecture support, such as for UML. But the most successful of these tools are IDEs.

## Contents

* 1 Uses of programming tools
* 1.1 Translating from human to computer language
* 1.2 Making program information available for humans
* 2 List of tools
* 3 IDEs
* 4 See also
* 5 References
* 6 External links

## Uses of programming tools

### Translating from human to computer language

Modern computers are very complex and in order to productively program them, various abstractions are needed. For example, rather than writing down a program's binary representation a programmer will write a program in a programming language like C, Java or Python. Programming tools like assemblers, compilers and linkers translate a program from a human write-able and readable source language into the bits and bytes that can be executed by a computer. Interpreters interpret the program on the fly to produce the desired behavior.

These programs perform many well defined and repetitive tasks that would nonetheless be time consuming and error-prone when performed by a human, like laying out parts of a program in memory and fixing up the references between parts of a program as a linker does. Optimizing compilers on the other hand can perform complex transformations on the source code in order to improve the execution speed or other characteristics of a program. This allows a programmer to focus more on higher level, conceptual aspects of a program without worrying about the details of the machine it is running on.

### Making program information available for humans

Because of the high complexity of software, it is not possible to understand most programs at a single glance even for the most experienced software developer. The abstractions provided by high-level programming languages also make it harder to understand the connection between the source code written by a programmer and the actual program's behaviour. In order to find bugs in programs and to prevent creating new bugs when extending a program, a software developer uses some programming tools to visualize all kinds of information about programs.

For example, a debugger allows a programmer to extract information about a running program in terms of the source language used to program it. The debugger can compute the value of a variable in the source program from the state of the concrete machine by using information stored by the compiler. Memory debuggers can directly point out questionable or outright wrong memory accesses of running programs which may otherwise remain undetected and are a common source of program failures.

## List of tools

Software tools come in many forms:

* Binary compatibility analysis tools
* Bug databases: Comparison of issue tracking systems - Including bug tracking systems
* Build tools: Build automation, List of build automation software
* Call graph
* Code coverage: Code coverage.
* Code review: List of tools for code review
* Compilation and linking tools: GNU toolchain, gcc, Microsoft Visual Studio, CodeWarrior, Xcode, ICC
* Debuggers: Debugger. See also Debugging.
* Disassemblers: Generally reverse-engineering tools.
* Documentation generators: Comparison of documentation generators, help2man, Plain Old Documentation, asciidoc
* Formal methods: Mathematical techniques for specification, development and verification
* GUI interface generators
* Library interface generators: SWIG
* Integration Tools
* Memory debuggers are frequently used in programming languages (such as C and C++) that allow manual memory management and thus the possibility of memory leaks and other problems. They are also useful to optimize efficiency of memory usage. Examples: dmalloc, Electric Fence, Insure++, Valgrind
* Parser generators: Parsing
* Performance analysis or profiling: List of performance analysis tool
* Revision control: List of revision control software, Comparison of revision control software
* Scripting languages: PHP, Awk, Perl, Python, REXX, Ruby, Shell, Tcl
* Search: grep, find
* Source code Clones/Duplications Finding: Duplicate code
* Source code editor
* Text editors: List of text editors, Comparison of text editors
* Source code formatting: indent, pretty-printers, beautifiers, minifiers
* Source code generation tools: Automatic programming
* Static code analysis: lint, List of tools for static code analysis
* Unit testing: List of unit testing frameworks

## IDEs

Integrated development environments combine the features of many tools into one package. They for example make it easier to do specific tasks, such as searching for content only in files in a particular project. IDEs may for example be used for development of enterprise-level applications.

Different aspects of IDEs for specific programming languages can be found in this comparison of integrated development environments.

## See also

* Computer aided software engineering tools
* Computer science
* Configuration System
* Scripting language
* Software development kit
* Software engineering and list of software engineering topics
* Software systems
* Toolkits for User Innovation

## References

* Software Development Tools for Petascale Computing Workshop 2007
* Kernighan, Brian W.; Plauger, P. J. (1976), Software Tools, Addison-Wesley, pp. 352, ISBN 0-201-03669-X, https://archive.org/details/softwaretools00kern/page/352

## External links

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Software engineering

Fields|

* Computer programming
* Requirements engineering
* Software deployment
* Software design
* Software maintenance
* Software testing
* Systems analysis
* Formal methods

Concepts|

* Data modeling
* Enterprise architecture
* Functional specification
* Modeling language
* Orthogonality
* Programming paradigm
* Software
* Software archaeology
* Software architecture
* Software configuration management
* Software development methodology
* Software development process
* Software quality
* Software quality assurance
* Software verification and validation
* Structured analysis

Orientations|

* Agile
* Aspect-oriented
* Object orientation
* Ontology
* Service orientation
* SDLC

Models|

| Developmental|

* Agile
* EUP
* Executable UML
* Incremental model
* Iterative model
* Prototype model
* RAD
* UP
* Scrum
* Spiral model
* V-Model
* Waterfall model
* XP

|

Other|

* SPICE
* CMMI
* Data model
* ER model
* Function model
* Information model
* Metamodeling
* Object model
* Systems model
* View model

Languages|

* IDEF
* UML
* USL
* SysML

Software
engineers

* Victor Basili
* Kent Beck
* Grady Booch
* Fred Brooks
* Barry Boehm
* Peter Chen
* Danese Cooper
* Ward Cunningham
* Tom DeMarco
* Edsger W. Dijkstra
* Delores M. Etter
* Martin Fowler
* Adele Goldstine
* Margaret Hamilton
* C. A. R. Hoare
* Lois Haibt
* Mary Jean Harrold
* Grace Hopper
* Watts Humphrey
* Michael A. Jackson
* Ivar Jacobson
* Alan Kay
* Nancy Leveson
* Stephen J. Mellor
* Bertrand Meyer
* David Parnas
* Trygve Reenskaug
* Winston W. Royce
* James Rumbaugh
* Mary Shaw
* Peri Tarr
* Elaine Weyuker
* Niklaus Wirth
* Edward Yourdon

Related fields|

* Computer science
* Computer engineering
* Project management
* Risk management
* Systems engineering

* Category
* Commons

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