Software engineering development process: the meiotic model

1. Software engineering development process: the meiotic model Vito Veneziano

2. What this talk is about (a disclaimer!) • A critical review of Software Engineering approaches • A hypothesis to re-organise software engineers’ job • A new biology-based view of how to model and develop software systems

3. Software processes: 3 phases • Software Engineering: • Definition phase – what? • Development phase – how? • Support and change phase – • Error correction • Adaptions • Enhancements Sounds like BIOLOGY?!

4. A list of process models • The waterfall model • Activities represented as separate process phases • Incremental development • Systems developed as a series of versions • Reuse-oriented software engineering • Based on identification and integration of reusable components • Agile methods

5. What all software engineering process models share is

6. CONTROL

7. But... What’s software engineering about, really? • Software engineering is about designing information systems that meet users’ viewpoints • There is no such a thing like an “absolute” system: it’s all about decisions to be made • Inherently constructionist approach

8. Engineering processes as problem analysis 1 • Problem analysis and solving is more than decomposing problems into sub-problems • Software engineers are expected to actively identify and decide about... • Contexts and context-sensitive meanings • General features and recurrent patterns • Relevant factors from the surroundings (ethics, cultural issues, economics, etc...) • Whose perspective that problem is “a problem”

9. Engineering processes as problem analysis 2 • ... In one word: software engineers have an active role to play in “finding” new, hidden information from within existing information • Sometimes “finding” means... “creating” • And... problems evolve Sounds like BIOLOGY?!

10. Nature VS Engineering • Nature solves “problems” (or should we call them challenges) without “obsessions” • It lets “solutions” evolve out of problems by encouraging diversity, independent assortment, genetic recombination • It makes problem solving “self-rewarding” • It obtains big solutions (complex eco-biological systems) from small processes (cells reproduction)

11. Problem analysis as cell reproduction processes? Identify relevant “chunks” of information (set of chromosomes) Mix them and further recombine into new “chunks” (crossing over) Split them into “bricks of information” (chromosome segregation), leading to the production of gametes Building new “chunks” by joining different “bricks” (zygotes from gametes)

12. Coat-colorgenes Eye-colorgenes • How crossing over leads to genetic recombination • Nonsister chromatids break in two at the same spot • The 2 broken chromatids join together in a new way Tetrad(homologous pair ofchromosomes in synapsis) Breakage of homologous chromatids 1 Joining of homologous chromatids 2 Chiasma Separation of homologouschromosomes at anaphase I 3 Separation of chromatids atanaphase II and completion of meiosis 4 Parental type of chromosome Recombinant chromosome Recombinant chromosome Parental type of chromosome Gametes of four genetic types

13. Software engineering and computer science... • … know something about cells and genetics, as they tend to apply biology-derived models to almost everything • Genetic Algorithms • Neural networks • Computational simulations of complex systems And what if they try...

14. Applying the meiotic model to S/W Eng own “core” activities • Could S/W Engineers tasks and individual skills be seen as the informational chunks that can be randomically “recombined” by an organisational crossing over process? • Would we end up with less control, but more diversity and variability? How? • How could testing evolve as well (and become more “demanding” and selective)?

15. Within the core process of engineering software... • S/W Engineering main task is to develop (i.e., “decide”) what information structure would make our systems best • Obviously, most of designing techniques have been derived by “engineering” approaches (class diagrams, use case diagrams, sequence diagrams, data flow diagrams), as if building information systems is the same as building “things” (which is less obvious, though!)

16. Biology is mainly about information systems • Every biological organism is an information system, exchanging information with[in] the environment and with other systems • Advanced biological systems have adopted the meiotic process to reproduce themselves AND IMPROVE the species they belong to Sounds like S/W Eng?!

17. [Information] environment A typical information management system... The world, society, etc etc Our system to be designed Other systems Customers Deliveries Payments Orders Products Staff Information chunks

18. A zoom on a typical information chunk (CRUD) [System] environment Customers Create Data Delete Retrieve Update

19. A new approach to software engineering? • Every information(al) chunk could be recombined whilst creating the whole system (new chunks expected!) • Customer-Orders • Staff-Deliveries • Deliveries-Products • Chunks exchange data • Information system grows... Sounds like Biology?!

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21. Thank you