Lectur e 7 - University of Texas at Austinusers.ece.utexas.edu/~miryung/teaching/EE382V-Spring2009...EE382V Softwar e Ev olution: Spring 2009, Instructor Mir yung Kim Kemer er and

EE382V Software Evolution: Spring 2009, Instructor Miryung Kim

Lecture 7Empirical Studies of Software Evolution: Change Types

Adaptive, Corrective, and Perfective Changes


Agenda

• Presentation on Kemerer and Slaughter’s paper

• Discussion on Kemerer and Slaughter’s paper


Change Types

• Adaptive changes: add new functionality to a system

• Corrective changes: fix faults in the software

• Perfective changes: improve developer’s ability to maintain the software without altering functionality or fixing faults


Today’s Presenter

• Arasi Aravindhan


Problem Definition

• Identify and understand the phases of software evolution


What are the differences between [Eick et al, TSE 2001] and [Kemerer and

Slaughter 1999]

• Kemerer’s paper focused more on justifying & choosing an approach

• Building models that help us understand software evolution

• Data sets: abundant, detail data, unique rich data produced by following rigorous process.

• quantitative -- statistics, math focused, qualitative


Kemerer and Slaughter [TSE, 2001]

• It is an *empirical study paper*

• No concrete hypotheses. In fact, the goal of this type of research is to identify hypotheses, and to discover a theory of the process of software evolution

• Often seen in grounded theory, ethnography, etc.

• It is also a survey paper of research methods in studying software evolution.


Sideway Discussion: How to write a good survey paper

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=> (1) Longitudinal study of (2) rich data from actual, business systems in real organization is required.


Study Approach

• Data Collection & Data Transformation

• Identify Measurement Variables

• Analysis

• Time Series Analysis

• Sequence Analysis

• Phase Mapping


Study Approach: (1) Data Collection

• Some retailer system written in Cobol

• Stability of development & management teams

• 20 years of data collection

• 25000 change log events

• module, author, function, date

• english description of the change


Study Approach: (2) Data Transformation

• Three independent coders manually coded change log data using content analytic approach

• To maximize inter-rater reliability,

• A standard coding procedure was developed.

• Several trial data coding processes were performed and Cohen’s K measure improved 0.42 to 0.78.


Study Approach: (3)-1 Time Series Analysis

• Identification of a quantified, continuous variable:

• # of changes per time period

• Per year => not sufficient number of time periods

• Per week or day => not sufficient number of changes per time period

• ARIMA (autoregressive integrated moving average)

• Data were not stationary

• Data series occurred in a largely random fashion


Study Approach: (3)-2 Sequence Analysis used in Social

Science

• Identification sequences of acts or phases from a long series of categorical data

• Phase mapping

• group by four consecutive events of the same type

• gamma sequence analysis -- Goodman-Kruskal score that assesses the proportion of phase order


Results from Sequence Analysis

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Threats to Validity

• External Validity: Does this work generalize to other situations?

• Construct Validity: Was the manual labeling /categorization process reliable and reproducible? Did programmers follow a rigorous data collection procedure?

• Conclusion Validity: Would the authors get the same results by grouping events with n consecutive events instead of 4 and by using a different parameter for phase analysis?


Any surprising results?

• More than 60% were enhancement and perfective changes.

•


My general thoughts on Kemerer and Slaughter [TSE, 1999]

• A highly disciplined qualitative study approach

• Attempt to understand software evolution processes from bottom-up using qualitative methods

• Nice attempt to incorporate change types

• In-depth, longitudinal study of two systems

• Results are hard to understand --- It is difficult to find any meaningful conclusions from the phase maps and gamma tables

Documents

Lectur e 7 - University of Texas at Austinusers.ece.utexas.edu/~miryung/teaching/EE382V-Spring2009...EE382V Softwar e Ev olution: Spring 2009, Instructor Mir yung Kim Kemer er and