Experimental Software Design

8/2/2019 Experimental Software Design

1/14

ExperimentalSoftware Design

Soham Thaker

Masters-Automation & IT

FH-Kln

Under the guidance ofProf. Bongards


2/14

Topics to be discussed:

What is Experimental Software Engineering (ESE)? Definition.

History Experimental Paradigm

Process of ESE

Examples Conclusion

References


3/14

What is Experimental Software Engineering?

Development of an experimental paradigm for evolving knowledge ofthe discipline & do research in order to achieve a scientific progressis known as Experimental Software Engineering.

Needs to follow the model like that of other physical sciences.

Example: Any Project development through Waterfall Model.

Analysis Design Implementation Test Evaluation

ProblemModel

SolutionModel Coding

CheckIntegrity

Completeas a whole

No. of User i/ps

Type of Project

UserRequirements

Time of Project

Team Size

Planning therequirements

CodingParameters

No. of Lines ofcode

Loops , etc

No.of Bugs

Types of Bugs

Number & typesof Defects.


4/14

History of Experimental SoftwareEngineering

Evolution done in early 1970s.

Phase-wise Developments: 1974-1985: Isolated studies done for particular purpose.

1986-1999: Building S/w processes & technical knowledge in specefic domains &environments.

2000-2005: Expanding studies out across other domains & environments but limitingthe technologies being studied.

2006 till now: Building knowledge about a specific domain using many technologiesand then integrating these domain specific know ledges.


5/14

Experimental Paradigm ESE- a research that helps establish a scientific & engineering basis

for the s/w engineering field.

ESE entails an Experimental Paradigm which involves ExperimentalDesign, Observation, Data collection through measurement andValidation of the process.

Experimental Method is to understand the effects of a particular tool

usage in some environment & to validate hypothesis about how bestthe s/w engineering can be accomplished.

1) The Scientific method: observe the world, propose a model or atheory of behavior, measure and analyze, validate hypotheses of the

model or theory, and if possible repeat the procedure.

Hypothesis Experiments Result DataCollection

Conclusions


6/14

Experimental Paradigm-2

1.1) The Engineering method: observe existing solutions, propose bettersolutions, build/develop, measure and analyze, and repeat the process untilno more improvements appear possible.

1.2) The Empirical method: propose a model, develop statistical/qualitativemethods, apply to case studies, measure and analyze, validate the modeland repeat the procedure.

2) The Mathematical method: propose a formal theory or set ofaxioms, develop a theory, derive results and if possible compare withempirical observations.


7/14

Process of ESE

1. Build Project Variables:

i. Identify the Project variables that affect the project. E.g.: ProjectTime, Success, Reliability, customer satisfaction, etc.

ii. Understand the variables

iii.Build Models using the variables to understand & characterize theenvironment.

2. Identify where the methods might make a difference.

3. Collecting data from live projects through measurement.

4. Feedback on data collection.

5. Storage and analysis of large amounts of data.


8/14

Example of Technology Transfer at Motorola

Adopted Goal-Question-Metric Paradigm

Adopted the Quality Improvement Paradigm, a three part process-improvement approach. (Planning, execution, and analysis andpackaging)

identify, tailor, and transfer software-engineering technology.

process package which evolves over time

Motorola set a 3-stage Formal-Software Review Process Preparation, Meeting & Follow-up

Review Goals, Review Metrics, Analyze Metrics


9/14

Quality Improvement Paradigm @ Motorola


10/14

Results of Technology Transfer at Motorola-(i)


11/14

Results of Technology Transfer at Motorola-(ii)

Phase Containment Effectivness of above table at each phase.


12/14

Conclusion

Does the experimental approachmake sense?

Many decisions were made in thepast, with compelling arguments,but without real proof

Of course logical arguments

should not be neglected, butinstead validated by experiments


13/14

References: The Past, Present, and Future of Experimental Software Engineering by Victor Robert

Basili. (Springer)

Experimental Software Engineering Issues: Critical Assessment and FutureDirections - International Workshop Dagstuhl Castle, Germany, September 14-18,1992 Proceedings ( Springer-Verlag)

Technology Transfer at Motorola Victor Basili, Daskalantonakis &Yacobellis. (IEEEJOURNAL)

Experimental Software Engineering: A Report on the State of the Art LawrenceVotta, Adam Porter & Dewayne Perry. (Springer)

Guide to Advanced Empirical Software Engineering Shull, F.; Singer, J.;Sjoeberg, D.

The Experimental Paradigm in Software Engineering - William W. Agresti, Victor R.Basili.


14/14

Any Questions?

THANK YOU !!!

Documents

Experimental Software Design