Software Engineering Research Approaches

Balancing theory and praxisHow engineering research differs

from scientific researchThe role of empirical studiesModels for SE research

The need to link research with practice

Why after 25 years of SE has SE research failed to influence industrial practice and the quality of resulting software?

Potts argues that this failure is caused by treating research and its application by industry as separate, sequential activities.

What he calls the research-then-transfer approach. The solution he proposes is the industry-as-laboratory approach.

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Colin Potts, Software Engineering Research Revisited, IEEE Software, September 1993

Research-then-Transfer

Incremental Refinementof research solutions

Problem evolves invisibly to the research community

ProblemV1

Wide gulf bridgedby indirect, anecdotal knowledge

ResearchSolutionV1

Technologytransfer Gapbridged byhard, but frequentlyinappropriate technology

ProblemV2

ProblemV3

ProblemV4

ResearchSolutionV2

ResearchSolutionV3Research

SolutionV4

Research-then-Transfer Problems

Both research and practice evolve separately

Match between current problems in industry and research solutions is haphazard

No winners

Disadvantages of Research-then-Transfer Research problems described and understood in terms of

solution technology - whatever is current research fashion. Connection to practice is tenuous.

Concentration is on technical refinement of research solution - OK but lacks industrial need as focus, so effort may be misplaced.

Evaluation is difficult as research solutions may use technology that is not commonly used in industry

Delay in evaluation means problem researchers are solving has often evolved through changes in business practice, technology etc.

Transfer is difficult because industry has little basis for confidence in proposed research solution.

Industry-as-Laboratory Approach to SE research

ProblemV2

Problem

V1

Problem

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Problem

V4

ResearchSolution

V1

ResearchSolution

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ResearchSolution

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ResearchSolution

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Advantages of Industry-as-Laboratory Approach

Stronger connection at start because knowledge of problem is acquired from the real practitioners in industry, often industrial partners in a research consortium.

Connection is strengthened by practitioners and researchers constantly interacting to develop the solution

Early evaluation and usage by industry lessens the Technology Transfer Gap.

Reliance on Empirical Research shift from solution-driven SE to problem-focused SE solve problems that really do matter to practitioners

Early SEI industrial survey research

What a SEI survey* learned from industry: There was a thin spread of domain knowledge in most

projects Customer requirements were extremely volatile.

These findings point towards research combining work on requirements engineering with reuse - instead of the approach of researching these topics by separate SE research communities - as is still found today!

*From ‘A field study of the Software Development Process

for Large Systems’, CACM, November 1988.

Further Results from Potts et al Early 90s Survey23 software development organizations (during 1990-92).

(Survey focused on Requirements Modeling process)

Requirements were invented not elicited. Most development is maintenance. Most specification is incremental. Domain knowledge is important. There is a gulf between the developer and user User-interface requirements continually change. There is a preference for office-automation tools

over CASE tools to support development. I.e. developers found using a WP + DB more useful than any CASE tools.

Industry-as-Laboratory emphasizes Real Case Studies

Advantages of case studies over studying problems in research lab.

Scale and complexity - small, simple (even simplistic) cases avoided - these often bear little relation to real problems.

Unpredictability - assumptions thrown out as researchers learn more about real problems

Dynamism - a ‘real’ case study is more vital than a textbook account

The real-world complications of industrial case studies are more likely to throw up representative problems and phenomena than research laboratory examples influenced by the researchers’ preconceptions.

Need to consider Human/Social Context in SE research

Not all solutions in software engineering are solely technical.

There is a need to examine organizational, social and cognitive factors systematically as well.

Many problems are “people problems”, and require “people-orientated” solutions.

Theoretical SE researchWhile there is still a place for innovative, purely

speculative research in Software Engineering, research which studies real problems in partnership with industry needs to be given a higher profile.

These various forms of research ideally complement one another.

Neither is particularly successful if it ignores the other.Too industrially focused research may lack adequate

theory!

Academically focused research may miss the practice!

Research models for SE

Problem highlighted by Glass*: Most SE Research in 1990s was Advocacy

Research. Better research models needed.

The software crisis provided the platform on which most 90s research was founded.

SE Research ignored practice, for the most part; lack of practical application and evaluation were gapping holes in most SE research.

Appropriate research models for SE are needed.* Robert Glass, The Software -Research Crisis, IEEE Software, November 1994

Methods underlying Models

Scientific method

Engineering method

Empirical method

Analytical methodFrom W.R.Adrion, Research Methodology in Software

Engineering, ACM SE Notes, Jan. 1993

Scientific method

Observe real world

Propose a model or theoryof some real world phenomena

Measure and analyzeabove

Validate hypotheses of the model or theory

If possible, repeat

Engineering method

Observe existing solutions

Propose better solutions

Build or develop bettersolution

Measure, analyze, andevaluate

Repeat until no further improvements are possible

Empirical method

Propose a model

Develop statistical or otherbasis for the model

Apply to case studies

Measure and analyze

Validate and then repeat

Analytical method

Propose a formal theory or set ofaxioms

Develop a theory

Derive results

If possible, compare withempirical observations

Refine theory if necessary

Need to move away from purely analytical method

The analytical method was the most widely used in mid-90s SE research, but the others need to be considered and may be more appropriate in some SE research.

Good research practice combines elements on all these approaches.

4 important phases for any

SE research project (Glass)

Informational phase - Gather or aggregate information via reflection literature survey people/organization survey case studies

Propositional phase - Propose and build hypothesis, method or algorithm, model, theory or solution

Analytical phase - Analyze and explore proposal leading to demonstration and/or formulation of principle or theory

Evaluation phase - Evaluate proposal or analytic findings by means of experimentation (controlled) or observation (uncontrolled, such as case study or protocol analysis) leading to a substantiated model, principle, or theory.

Software Engineering Research Approaches

The Industry-as-Laboratory approach links theory and praxis

Engineering research aims to improve existing processes and/or products

Empirical studies are needed to validate Software Engineering research

Models for SE research need to shift from the analytic to empirical.