2016Unpublished venueRequires access

Quantifying Productivity of Individual Software Programmers: Practical Approach

Mehmet S. Unluturk, Kaan Kurtel

Open publisher page 8 citations

Abstract

Software measurement is a crucial part of a good software engineering. Software developers quantify the software to see if the use cases are complete, if the analysis model is consistent with requirements and if the code is ready to be tested. Software project managers assess the software process and the software product to determine if it is going to be finished on time and within budget. Customers evaluate the final product if it meets their needs. Overall, the main purpose of software engineering is to make software systems controllable and foreseeable, activities with a solid method rather than intuitional, complicated or unprincipled. Software measurement studies are about quantifying the software engineering entities and attributes, both of which aim to support software development efforts and quality improvement. In this paper, we quantify a set of relationships using the current size, defect and object-oriented software metrics practically and pragmatically. Our paper proposes a method to measure the productivity of individual software programmers. Furthermore, this method provides a common opinion for understanding, controlling and improving the software engineering practices.

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What this paper is about

Software measurement is a crucial part of a good software engineering. Software developers quantify the software to see if the use cases are complete, if the analysis model is consistent with requirements and if the code is ready to be tested. Software project managers assess the software process and the software product to determine if it is going to be finished on time and within budget. Customers evaluate the final product if it meets their needs. Overall, the main purpose of software engineering is to make software systems controllable and foreseeable, activities with a solid method rather than intuitional, complicated or unprincipled. Software measurement studies are about quantifying the software engineering entities and attributes, both of which aim to support software development efforts and quality improvement. In this paper, we quantify a set of relationships using the current size, defect and object-oriented software metrics practically and pragmatically. Our paper proposes a method to measure the productivity of individual software programmers. Furthermore, this method provides a common opinion for understanding, controlling and improving the software engineering practices.

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OpenAlex reports 8 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Software measurement is a crucial part of a good software engineering. Software developers quantify the software to see if the use cases are complete, if the analysis model is consistent with requirements and if the code is ready to be tested. Software project managers assess the software process and the software product to determine if it is going to be finished on time and within budget. Customers evaluate the final product if it meets their needs. Overall, the main purpose of software engineering is to make software systems controllable and foreseeable, activities with a solid method rather than intuitional, complicated or unprincipled. Software measurement studies are about quantifying the software engineering entities and attributes, both of which aim to support software development efforts and quality improvement. In this paper, we quantify a set of relationships using the current size, defect and object-oriented software metrics practically and pragmatically. Our paper proposes a method to measure the productivity of individual software programmers. Furthermore, this method provides a common opinion for understanding, controlling and improving the software engineering practices.

Key concepts: Software sizing, Software construction, Software engineering, Personal software process, Computer science, Software development, Social software engineering, Verification and validation

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