Software errors and complexity: an empirical investigation0
Communications of the ACM
Software engineering metrics and models
Software engineering metrics and models
Experimentation in software engineering
IEEE Transactions on Software Engineering
Software Engineering Institute and Wang Institute of Graduate Studies on Software engineering education: the educational needs of the software community
The master of software engineering program at Seattle University after six years
Software Engineering Institute and Wang Institute of Graduate Studies on Software engineering education: the educational needs of the software community
An empirical validation of software cost estimation models
Communications of the ACM
Software reliability: measurement, prediction, application
Software reliability: measurement, prediction, application
Software metrics: establishing a company-wide program
Software metrics: establishing a company-wide program
Evaluating Software Complexity Measures
IEEE Transactions on Software Engineering
Managing the software process
IEEE Transactions on Software Engineering
The dimensionality of program complexity
ICSE '89 Proceedings of the 11th international conference on Software engineering
Design complexity measurement and testing
Communications of the ACM
Software Size Estimation of Object-Oriented Systems
IEEE Transactions on Software Engineering
Software metrics in the process maturity framework
Journal of Systems and Software - An Oregon workshop on software metrics
Software complexity: measures and methods
Software complexity: measures and methods
Object-oriented software engineering
Object-oriented software engineering
Object-oriented analysis (2nd ed.)
Object-oriented analysis (2nd ed.)
Practical software metrics for project management and process improvement
Practical software metrics for project management and process improvement
Quality software management (vol. 2): first-order measurement
Quality software management (vol. 2): first-order measurement
Software engineering metrics I: measures and validations
Software engineering metrics I: measures and validations
A practical guide to logical data modeling
A practical guide to logical data modeling
Object-oriented analysis and design with applications (2nd ed.)
Object-oriented analysis and design with applications (2nd ed.)
IEEE Software
Property-Based Software Engineering Measurement
IEEE Transactions on Software Engineering
Object-oriented development process and metrics
Object-oriented development process and metrics
Software metrics (2nd ed.): a rigorous and practical approach
Software metrics (2nd ed.): a rigorous and practical approach
Measuring software reuse: principles, practices, and economic models
Measuring software reuse: principles, practices, and economic models
Software quality classification model based on McCabe's complexity measure
Journal of Systems and Software - Special issue on achieving quality in software
A Review and Evaluation of Software Science
ACM Computing Surveys (CSUR)
Death March: The Complete Software Developer's Guide to Surviving "Mission Impossible" Projects
Death March: The Complete Software Developer's Guide to Surviving "Mission Impossible" Projects
A Discipline for Software Engineering
A Discipline for Software Engineering
Software Engineering Economics
Software Engineering Economics
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Software Engineering: A Practitioner's Approach
Software Engineering: A Practitioner's Approach
Software Risk Management: Principles and Practices
IEEE Software
Software Process Improvement At Raytheon
IEEE Software
Cleanroom Process Model: A Critical Examination
IEEE Software
Point: Why We Should Use Function Points
IEEE Software
Counterpoint: The Problem with Function Points
IEEE Software
Status Report on Software Measurement
IEEE Software
Establishing Software Measurement Programs
IEEE Software
Implementing Effective Software Metrics Programs
IEEE Software
How Software Process Improvement Helped Motorola
IEEE Software
Software Measurement: A Necessary Scientific Basis
IEEE Transactions on Software Engineering
A Metrics Suite for Object Oriented Design
IEEE Transactions on Software Engineering
Third time charm: Stronger prediction of programmer performance by software complexity metrics
ICSE '79 Proceedings of the 4th international conference on Software engineering
Measuring commercial PL/I programs using Halstead's criteria
ACM SIGPLAN Notices
Principles of Program Design
Controlling Software Projects: Management, Measurement, and Estimates
Controlling Software Projects: Management, Measurement, and Estimates
Structured Analysis and System Specification
Structured Analysis and System Specification
Structured programming
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As a recognized discipline, software engineering traces its roots back to the 1968 NATO conference where the term was first used extensively to highlight the need for an engineering approach to the development of software. In the 30 years since that first “software engineering” conference, significant attempts have been made to improve the overall effectiveness of the software development process, and thus reduce the frequency and severity of software project failures. A major part of this improvement effort has been the attempt to develop quantitative measures which can be used to more accurately describe and better understand and manage the software development life cycle. Thus, many software metrics and models have been introduced during this period. In this article, we briefly trace the history of the development of software metrics and models, and then summarize the current state of the field. For discussion purposes, this entire development period is then arbitrarily divided into an Introductory Period (1971–1985), Growth Period (1985–1997) and the Current Period (1997–?). The development of metrics during each of these periods is then related to the treatment of software metrics and models in software engineering curricula during that same period. Our conclusion is that software engineering curricula have indeed reflected the state of software engineering as the work in software metrics and models has progressed. Furthermore, software engineering curricula of the future should reflect the relatively mature state that software metrics have attained, by covering the basic concepts of metrics in appropriate core courses, and more advanced metrics topics in a specialized, elective metrics course.