KR20040024925A - Software Productivity Measurement Methods and Systems - Google Patents

Abstract

PURPOSE: A method and a system for measuring a productivity of software are provided to make business engineering for software development and maintenance easy by measuring/predicting the productivity of the software, and to enhance a chance of success by performing the related managements through project management. CONSTITUTION: An object/environmental variable input part(A01) automatically measures the productivity of the software. A development manpower analysis engine(A02) analyzes a characteristic of development manpower and extracts the information for measuring the productivity. A development process analysis engine(A03) analyzes a characteristic of a development process and extracts the information for measuring the productivity. A productivity measuring matrix database(A06) manages a standard for measuring the productivity. A productivity predicting model-base(A07) manages a productivity predicting model used for predicting the productivity. A productivity measuring knowledge-base(A08) manages a rule, a procedure, and knowledge needed to measure the productivity. A productivity measuring engine(A09) measures the productivity by the standard, the predicting model, and the extracted information.

Description

Software Productivity Measurement Methods and Systems

TECHNICAL FIELD The present invention belongs to the field of software metrics in software engineering, and relates to a method and system for measuring software productivity, and more particularly, to a method and system for measuring software productivity more consistently and accurately. The conventional method has a problem in that accuracy is insufficient by measuring software productivity subjectively and irrationally. Conventional software productivity measurement standards, procedures, guidelines, systems, etc. have caused a lot of problems in usability due to the emergence of new object technology or component technology, and the phenomenon of lack of accuracy and consistency of software productivity using them occurs. Therefore, the conventional technology is difficult to apply to the embedded productivity, semi-detached mode, or independent mode software productivity measurement by object technology or component technology. Conventional software productivity measurement methods are not well-formed and lack standards, procedures, guidelines and automation systems. Therefore, the conventional method cannot secure the objectivity, reliability and accuracy of software productivity measurement.

The technical problem to be achieved by the present invention is first, to improve the conventional subjective and unreasonable way of measuring software productivity, and to measure software productivity more accurately based on more objective and reasonable criteria, procedures, guidelines, and automated systems. And to provide a system. Second, it is an object of the present invention to provide a method and system for more accurately and consistently measuring embedded, semi-built and stand-alone software productivity. Third, an object of the present invention is to provide a method and system for more conveniently measuring the productivity of software developed by a procedure-oriented development method, an object-oriented development method, a component-based development method, and a reverse engineering method. Fourth, the problem to be achieved by the present invention is the object-oriented Unified Modeling Language or object-oriented programming language C ++, JAVA, IDL, Ada, C #, SQL, VB.NET, Python, It provides a way to more accurately measure software productivity based on SmallTalk. Finally, the task of the present invention is to efficiently and accurately measure or predict the productivity of the software to provide efficient engineering of the business for software development and operation, and to manage the project, scope management, contract management, cost management , Manpower management, schedule management, quality management, configuration management, risk management. It is to improve business success by carrying out communication management and integrated management more systematically and scientifically.

1 is a block diagram illustrating a software productivity measuring method and system according to an exemplary embodiment of the present invention, and FIG. 2 is a flowchart illustrating the operation of the software productivity measuring method and system according to an exemplary embodiment of the present invention.

Software productivity measurement method and system of the present invention, the measurement object and the environment variable input unit, development personnel analysis engine, development process analysis engine, development method and tool analysis engine, reusable component analysis engine, productivity Measurement metrics database, statistical productivity prediction model base, productivity measurement knowledge base which is a set of rules, guidelines and knowledge necessary for measurement or prediction of productivity, productivity measurement engine for measuring productivity based on the selected contents, and outputting the measurement result Characterized in that configured to include the measurement result output unit.

Referring to the accompanying drawings, preferred embodiments of the method and system for measuring software productivity according to the present invention will be described in detail as follows.

1 is a block diagram illustrating a software productivity measuring method and system according to an exemplary embodiment of the present invention, and FIG. 2 is a flowchart illustrating the operation of the software productivity measuring method and system according to an exemplary embodiment of the present invention.

Software productivity measurement method and system according to an embodiment of the present invention, as shown in Figure 1, the development personnel analysis engine for analyzing and extracting information that affects the measurement target and environment variable input unit (A01), and the productivity of the development personnel ( A02), a development process analysis engine (A03) that analyzes development processes to extract information that affects productivity, and a development method and tool analysis engine (A04) that analyzes development methods and tools to extract information that affects productivity To analyze the reused components available to the organization, extract the information that affects productivity, the reuse component analysis engine (A5), productivity measurement metrics database (A06), statistical productivity prediction model base (A07), Productivity measurement knowledge base (A08), which is a set of necessary rules, guidelines, and knowledge, to measure productivity based on the selections above Is step down configuration including the productivity measured engine (A09), the measurement result and outputting the measurement result output section (A10).

Here, the measurement object and environment variable input unit A01 inputs an environment variable for measuring productivity and information on processes, manpower, development methods and tools, and reusable components, which are production elements of software.

The development personnel analysis engine A02 analyzes and extracts information that affects the productivity of the development personnel. Here, the information affecting the productivity of the development personnel includes information that quantifies the related experience, knowledge, skills, attitudes, etc. of each participant's function.

The development process analysis engine A03 analyzes the development process to extract information affecting productivity. Here, the information on the development process that affects productivity is the maturity of the development process, which is divided into initial stage, repeatable stage, defined stage, managed stage, and optimized stage. Information for Information related to process maturity is analyzed and extracted according to International Standard (ISO 15504) and The Capability Maturity Model (CMM) of the Software Engineering Research Institute of Carnegie Mellon University.

The development method and tool analysis engine A04 analyzes the development method and tool and extracts information that affects productivity. Here, the information affecting the productivity of the development method and tools is carried out by the human resources management and engineering process, where the human resources are factors that overcome human limitations and improve human capabilities by using the development methods and tools It includes.

The reuse component analysis engine A5 analyzes the reuse components available to the organization and extracts information that affects productivity. Here, the reuse component includes a component that can be obtained through commercial purchase, a component managed in a library or a repository, a component developed for reuse, and a component provided as a system utility. Here, the concept of reuse includes full reuse and post-modification reuse, and also includes high level engineering output reuse and low level engineering output reuse.

The productivity measurement metrics database A06 provides a productivity measure and provides a measure of productivity by percentage and a measure of productivity index. Here, the concept of productivity is expressed on the scale of the software, taking into account the complexity produced for manpower administered per hour, day, month or year.

The statistical productivity prediction model base A07 is a set of models for predicting productivity using statistical probability theory and management science technique using information affecting the identified productivity. Here, the prediction model includes a deterministic problem solving method and a nondeterministic problem solving method.

The productivity measurement knowledge base A08 is a set of rules, guidelines, and knowledge necessary for measuring or predicting productivity.

The productivity measuring engine A09 performs productivity measurement by the information affecting the productivity. Here, the productivity measurement engine A09 performs productivity measurement through organic communication with the statistical productivity prediction model base A07 and the productivity measurement knowledge base A08.

The measurement result output unit A10 outputs the measurement result of the productivity measurement engine A08 by a screen or a printing method. Here, the above productivity measurement process can be repeated if necessary.

Operation of the productivity measurement method and system according to an embodiment of the present invention configured as described above is as follows.

First, as shown in FIG. 2, the characteristics of the development personnel, the characteristics of the development process, the characteristics of the development method and the tool, and the characteristics of the reuse component are input in the measurement object and the environment variable input unit A01. The measurement elements are identified in (B02), and the result is selected as a development personnel analysis engine (A02), a development process analysis engine (A03), a development method and tool analysis engine (A04), or a reusable component analysis engine (A05). .

If the measurement factor is manpower, the information necessary for productivity measurement is analyzed and extracted (B03) by the development personnel analysis engine (A02), and stored and provided to the productivity measurement engine (A09).

If the measurement element classification is a process, information necessary for productivity measurement is analyzed and extracted (B04) by the development process analysis engine (A03), and stored and provided to the productivity measurement engine (A09).

If the measurement element is a tool, information necessary for productivity measurement is analyzed and extracted (B05) by the development method and the tool analysis engine (A04), and stored and provided to the productivity measurement engine (A09).

If the measurement element classification is a component, information necessary for productivity measurement is analyzed and extracted (B06) by the reuse component analysis engine (A05), and stored and provided to the productivity measurement engine (A09).

Then, the productivity measurement engine A09 sets productivity criteria using the productivity measurement metrics database A06 or B07, selects the required model from the statistical productivity prediction model base A07 or B08, and selects the productivity measurement knowledge base ( A08 or B09) to measure the productivity (B10), and provides this to the measurement result output unit (A10).

Finally, the measurement result output unit A10 outputs the measurement result of productivity on the screen or printing paper (B11), and repeats the production measurement process if necessary.

The main effect of the present invention is to solve inaccuracies and difficult problems in measuring software productivity. In addition, even in the environment of various software applications, development methods, and programming languages, software productivity can be conveniently and automatically measured in a format desired by the user, thereby minimizing time and economic losses. In addition, the present invention is to provide a convenient and accurate measurement of software productivity to enable a more systematic and scientific approach to business management and engineering. In addition, the use or application of the present invention is enterprise management, engineering and project management, and in particular, it can greatly contribute to the development personnel management of software, the selection of development methods and tools.

Claims (2)

Measure or predict software productivity based on development personnel, processes, development methods and tools, and reused components that are administered when developing embedded, semi-built, and stand-alone software systems in a procedural, object-oriented, component-based, or programming language. In the method and system, An object and environment variable input unit for inputting related information to automatically measure software productivity; Development personnel analysis engine that analyzes characteristics of development personnel and extracts information to measure productivity; A development process analysis engine that analyzes the characteristics of the development process and extracts information for measuring productivity; Development method and tool analysis engine that analyzes characteristics of development method and tool and extracts information for measuring productivity; A reuse component analysis engine that analyzes characteristics of the reuse component and extracts information for measuring productivity; A productivity measurement metrics database for planning, creating, managing, and providing productivity metrics; A statistical productivity prediction model base for planning, creating, managing, and providing statistical or mathematical productivity prediction models used to predict productivity; A productivity measurement knowledge base that plans, creates, manages, and provides rules, procedures, and knowledge required for productivity measurement; A productivity measurement engine for measuring software productivity based on the measurement metrics, the selected prediction model, and the extracted characteristics; Software productivity method and system comprising a measurement result output unit for outputting the measurement results. The method of claim 1, The statistical productivity prediction model base is a set of models for predicting productivity using statistical probability theory and management science techniques. Here, the prediction model includes a deterministic problem solving method and a nondeterministic problem solving method.