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

2. 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. 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. 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. 5 What all software engineering process models share is

6. 6 CONTROL

7. 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. 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. 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. 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. 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. 12 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 of chromosomes in synapsis) Breakage of homologous chromatids Joining of homologous chromatids Chiasma Separation of homologous chromosomes at anaphase I Separation of chromatids at anaphase II and completion of meiosis Parental type of chromosome Recombinant chromosome Parental type of chromosome Gametes of four genetic types 1 2 3 4 Coat-color genes Eye-color genes

13. 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. 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. 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. 16 Biology is mainly about information systems Every biological organism is an information system, exchanging information with[in] the environment and with other systems Sounds like S/W Eng?! Advanced biological systems have adopted the meiotic process to reproduce themselves AND IMPROVE the species they belong to

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

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

19. 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?!

20. 20 ?

21. 21 Thank you