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• Programming_productivity abstract "Programming productivity refers to software development issues and methodologies affecting the quantity and quality of code produced by an individual or team. Key topics in productivity discussions have included: Amount of code that can be created or maintained per programmer (often measured in source lines of code per day) Detecting and avoiding errors (through techniques like Agile Software Development, six sigma management, zero defects coding, and Total Quality Management) Software cost estimation (cost being a direct consequence of productivity)The relative importance of programming productivity has waxed and waned along with other industry factors, such as: The relative costs of manpower versus machine a substantially less expensive global workforce is available via the Internet examples: http://www.wired.com/wired/archive/12.02/india.html?pg=7 http://www.wired.com/wired/archive/12.02/india.html The size and complexity of the systems being built Highly publicized projects that suffered from delays or quality problems Development of new technologies and methods intended to address productivity issues Quality management techniques and standards apathy may be a factor (productivity needs to be a goal)A generally accepted working definition of programmer productivity needs to be established and agreed upon. Appropriate metrics need to be established. Productivity needs to be viewed over the lifetime of code. Example: Programmer A writes code in a shorter interval than programmer B but programmer A's code is of lower quality and months later requires additional effort to match the quality of programmer B's code; in such a case, it is fair to claim that programmer B was actually more productive.Hardware aspects of programmer productivityIt is unfair to measure programmer productivity without factoring in the software and hardware tools that have been provided to the programmers being measured. Example: a programmer with two displays is likely to be more productive than a programmer with a single display. With solid state drives becoming less expensive, one's hardware can be fine tuned for faster compilation as is required by new development paradigms such as TDD (test driven development).An extensive literature exists dealing with such issues as software productivity measurement, defect avoidance and removal, and software cost estimation. The heyday of such work was during the 1960s-1980s, when huge mainframe development projects often ran badly behind schedule and over budget. A potpourri of development methodologies and software development tools were promulgated, often championed by independent consultants brought in as troubleshooters on critical projects. The U.S. Department of Defense was responsible for much research and development in this area, as software productivity directly affected large military procurements.In those days, large development projects were generally clean-sheet implementation of entire systems, often including their own system-level components (such as data management engines and terminal control systems). As a result, large organizations had enormous data processing staffs, with hundreds or thousands of programmers working in assembly language, COBOL, JOVIAL, Ada, or other tools of the day.Modern computer use relies much more heavily on the use of standardized platforms and products, such as the many general-purpose tools available today under Linux and the Microsoft operating systems. Organizations have more off-the-shelf solutions available, and computer use is a basic job requirement for most professionals. Tasks that once would have required a small development team are now tackled by a college intern using Microsoft Excel. The result has been a trend toward smaller IT staffs and smaller development projects. With larger projects, techniques like rapid prototyping have shortened development project timelines, placing a priority on quick results with iterative refinement. Traditional programming-in-the-large has thus become rare – the domain of industry giants like Microsoft and IBM. As a result, although programming productivity is still considered important, it is viewed more along the lines of engineering best practices and general quality management, rather than as a distinct discipline.A need for greater programmer productivity was the impetus for categorical shifts in programming paradigms. These came from Speed of code generation Approach to maintenance Emerging technologies Learning curve (training required) Approach to testing".
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• Programming_productivity wikiPageWikiLink Category:Software_engineering_costs.
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• Programming_productivity wikiPageWikiLink Test-driven_development.
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• Programming_productivity wikiPageWikiLink Total_Quality_Management.
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• Programming_productivity wikiPageWikiLink U.S._Department_of_Defense.
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• Programming_productivity wikiPageWikiLink Zero_Defects.
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• Programming_productivity wikiPageWikiLinkText "Programming productivity".
• Programming_productivity wikiPageWikiLinkText "programming productivity".
• Programming_productivity date "January 2013".
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• Programming_productivity comment "Programming productivity refers to software development issues and methodologies affecting the quantity and quality of code produced by an individual or team.".
• Programming_productivity label "Programming productivity".
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