COCOMO II Parameters and IDPD: Bilateral Relevances Ramin Moazeni Computer Science Department University of Southern California Los Angeles, U.S.A. moazeni@usc.edu Daniel Link Computer Science Department University of Southern California Los Angeles, U.S.A. dlink@usc.edu Barry Boehm Computer Science Department University of Southern California Los Angeles, U.S.A. boehm@usc.edu ABSTRACT The phenomenon called Incremental Development Productivity Decline (IDPD) is presumed to be present in all incremental software projects to some extent. COCOMO II is a popular parametric cost estimation model that has not yet been adapted to account for the challenges that IDPD poses to cost estimation. Instead, its cost driver and scale factors stay constant throughout the increments of a project. While a simple response could be to make these parameters variable per increment, questions are raised as to whether the existing pa- rameters are enough to predict the behavior of an incrementally developed project even in that case. Individual COCOMO II parameters are evaluated with regard to their development over the course of increments and how they influence IDPD. The reverse is also done. In light of data collected in recent experi- mental projects, additional new variable parameters that either extend COCOMO II or could stand on their own are proposed. Categories and Subject Descriptors D.2.9 [Software Engineering]: Management – cost estimation, life cycle, productivity. General Terms Management, Measurement, Economics, and Human Factors. Keywords Parametric cost estimation; IDPD; incremental development; cost drivers; scale factors 1. INTRODUCTION IDPD is the phenomenon of an overall productivity decline over the course of several increments. For the purposes of IDPD research, productivity is measured in SLOC/Effort. While SLOC are not an ideal measure of software productivity because they are not very useful in improving it [1], much useful work is not concerned with the creation or testing of code and different management perspectives should be taken into account when measuring productivity [2]. IDPD research uses them as a measure because they are subjective and difficult to measure. In addition, code churn, which includes debug code churn and refactoring code churn, is more associated with defect density than productivity [3] [4]. The IDPD between two increments is the percentage by which the productivity in SLOC/Effort is diminished between them. (If the productivity of a given increment is 80% of a given previous one, this is called an IDPD of 20%.) IDPD research is trying to answer the question of how much new output an organization can expect for a new increment. 1.1 Incremental Development This paper focuses on those incremental development projects whose increments are 1) more than one, 2) not less than a tenth of the previous one as expressed in SLOC (otherwise it will be counted with the previous one, 3) not just a bug fix of a previous increment, 4) each adding new functionality, and 5) depending on and coherent with previous increments. Section 2 describes the status of IDPD research. Section 3 gives an overview about software cost estimation. Section 4 looks at IDPD in relation to the COCOMO II cost estimation model and potential new pa- rameters. 2. Status of IDPD research The concept has been introduced with some first observations [3]. It has been found to be supported by Lehman’s Laws of Software Evolution [4]. Research remains to be done on several areas of interest such as IDPD variations between different project domains, a predictive model of IDPD and whether the choice of a life cycle model or other management influences can mitigate IDPD. 2.1 Research Methodology 2.1.1 Approach In order to arrive at a statistical model of IDPD, the attributes of increments as well as the parameters of the projects, their per- sonnel and their environments have to be collected. The collect- ed environmental data (cost drivers, scale factors) are then eval- uated with regard to their development over the course of incre- ments and whether additional new variable parameters are need- ed or to either extend COCOMO II existing parameters. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for prof- it or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, re- quires prior specific permission and/or a fee. (Depending on the chosen publication rights for the paper, ACM might send a text that slightly differs to the first author.) ICSSP'14, May 26–28, 2014, Nanjing, China Copyright 2014 ACM 978-1-4503-2754-1/14/05... $15.00.