Login

Publications  •  Project Statistics

Glossary  •  Schools  •  Disciplines
People Search: 
   
Title/Abstract Search: 

Dissertation Information for Chris F. Kemerer

NAME:
- Chris F. Kemerer

DEGREE:
- Ph.D.

DISCIPLINE:
- Information Systems

SCHOOL:
- Carnegie Mellon University (USA) (1987)

ADVISORS:
- None

COMMITTEE MEMBERS:
- None

MPACT Status: Incomplete - Not_Inspected

Title: Measurement of software development productivity

Abstract: One of the research topics for the 1990s that is of considerable importance to MIS researchers is the high cost of developing and maintaining software. As the demand for software continues to rise at a faster rate than our ability to train new information systems professionals, it becomes essential to improve the productivity of industry personnel. Key research issues therefore are the design of a productivity measurement system and the identification of the principal factors influencing productivity. The results are useful in providing managers with a guide to most efficiently using the resources available to them for software development.

Chapter 2 is a test of previous researchers' models on a data-set of completed new software development projects. Four cost estimation models are tested ex post on a set of fifteen large new development projects. The results are that the models may be of help to software practitioners in estimation, but they have not modeled the factors affecting productivity in the environment tested very well. Chapter 3 uses the same data-set for an exploration of the possibility of using a frontier analysis method for measuring software development productivity. A new model utilizing Data Envelopment Analysis (DEA) is developed and shown to be promising in identifying the relative productivity of software development projects.

Chapter 4 describes an important subset of the software development productivity measurement problem, the measurement of software maintenance productivity. This chapter develops a model for the measurement of software maintenance productivity and quality. Chapter 5 begins with a description of the data collection methods used to capture a data-set of 65 software maintenance projects. It also presents the results of estimating the DEA-based model developed in Chapter 4, including the evaluation of a number of factors expected to affect productivity. Chapter 6 summarizes some of the results of chapters 2-5 and discusses possible future avenues of research.

MPACT Scores for Chris F. Kemerer

A =
C =
A+C =
T =
G =
W =
TD =
TA =
calculated

Advisors and Advisees Graph