Software Engineering Experimentation Experimental Terms Jeff Offutt

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Presentation transcript:

Software Engineering Experimentation Experimental Terms Jeff Offutt

© Jeff Offutt, Do We Know This Already? We saw the basics of experimental design in 5th grade –Not many details –Many of us were not paying attention College students in science learn this in their freshman year –Physics, chemistry, biology, … A failing of CS is that we do not teach this material

© Jeff Offutt, Descriptive Research Observational studies : systematic measurement of behavior –Often subjective –Interrater reliability : degree to which independent observers agree on their coding of data Archival studies : examine records of past events and behaviors Surveys : asking questions about attitudes, beliefs, and behavior Used to discover trends and tendencies

© Jeff Offutt, Scientific Experiment Changes a set of variables to elicit a response Imposes a treatment on a group of objects or subjects –Treatment defines a way to change variables Example –Variable is the programming language –Treatment “changes” variable from C++ to Java Used to understand effects

© Jeff Offutt, Correlational Research Correlation coefficient : statistical measure of the strength and direction of association between two variables (varies between –1.0 and +1.0) –Positive correlation : As one variable increases the other also increases –Negative correlation : As one variable increases the other decreases –Zero correlation : The variables have no relationship Used to establish associations between variables

© Jeff Offutt, Basic Experimental Terms Hypothesis : A testable prediction about the conditions under which an event will occur Theory : An organized set of principles used to explain observed phenomena Operational Definition : A specific way in which a variable is measured or manipulated (treatment)

© Jeff Offutt, Experimental Variables Independent variable : Changed by the researcher to determine if it causes a change in the dependent variable Dependent variable : Measured by the researcher to determine if it is affected by the IV Confounding variables : Other explanations for the results –Experience, education, typing speed, tools used Measured variable : If the dependent variable cannot be directly measured, we measure a related variable to approximate –Faults, size of program, readability, … Does intelligence make people better programmers ? programmersintelligence

© Jeff Offutt, Validity 1.Internal validity : degree to which there is certainty that the IV caused the effects on the DV 2.External validity : degree to which the results from a study can be generalized to other situations and people 3.Conclusion validity : degree to which conclusions relationships in the data are reasonable 4.Construct validity : degree to which inferences can be made from the specific objects in your study to the theoretical constructs on which those objects were based

© Jeff Offutt, Experimental Bias Bias : A flaw in the experimental design or conduct that can change the dependent variable –This is often due to an inadvertent introduction of a confounding variable Bias (psychology): A flaw introduced by an experimenter whose expectations about the outcome of the experiment can be subtly communicated to the participants in the experiment –Often happens when experimenters are also subjects

© Jeff Offutt, Example Independent Variables : Data flow, branch testing Dependent Variable : Faults found Confounding Variables : tool support, characteristics of subjects, specific values chosen, knowledge of testers, … –Effects the internal validity Bias : If I invented data flow, I expect it to do better Data flow testing finds more faults than branch testing

© Jeff Offutt, Correlation and Causality Correlated : Two things always happen at the same time –Brake lights and car slowing down Causality : Understanding what causes something to happen –Brake light causes the car to slow down ? If A and B are correlated : AB causes AB A B C Pressing brake activates brake light AND slows car down …

© Jeff Offutt, Correlation and Prediction Correlation : if A happens, then B happens –Brake lights and car slowing down Causality : if A happens, then it causes B to happen –Pressing brake slows the car down Predictability : if A happens, I can predict that B will happen We do not need to show causality to have predictability

© Jeff Offutt, Mixing Correlation and Causality In “the old days”, we believed that being cold caused us to get colds Colds are caused by viruses, not temperature Viruses breed in warm, damp, low-oxygen, carbon-dioxide rich environments In cold weather, we close our windows and turn up the heat … creating … Virginia gets a secondary cold season in July-August … when the weather turns hot and humid …

© Jeff Offutt, Cognitive Dissonance We feel uncomfortable when new data or a new model contradicts a previously held model Revising our mental model to accommodate new data is hard –We resist the new idea Successful scientists are not bothered by cognitive dissonance –Vive la difference!

© Jeff Offutt, Experimental Design Choosing variables, subjects, objects, process and analysis method Pilot study : small-scale experiment used to design the full experiment –Identify potential confounding variables –Refine experimental design

© Jeff Offutt, Avoiding Bias in Experimental Design Control : Ensuring the confounding variables do not influence the results –I want to measure whether maintenance programmers understand programs better by studying statecharts or reading comments –Comments already existed in the program, statecharts generated by experimenter –Statecharts were of much higher quality –Programmers understood statecharts better … Must control for differences in quality

© Jeff Offutt, Avoiding Errors of Judgment Randomization : Objects are assigned randomly to experimental groups –Randomized block design : Divide subjects into homogeneous blocks, then randomly assign from each block Programmers : undergraduate students, MS students, PhD students, professional Replication : Perform the experiment again, with different subjects, experimenters, or experiment design –Many reviewers will not accept replicated experiments

© Jeff Offutt, Placebos in Experimental Design Patients expect a treatment to work, and sometimes respond to a treatment that has no effect – like a sugar pill Programmers in an experiment will do better because they think they should – they concentrate better or work harder –Give some programmers a tool that actually does not work Double-blind : Neither the programmers or the experimenter knows who has the placebo

© Jeff Offutt, Hawthorne Effect When people know they are being studied, they will behave differently How can we study people without letting them know they are being studied?

Summary © Jeff Offutt, These terms need to be part of your normal vocabulary