How Software Engineering Can Benefit from Traditional Industries Practical Experience Report ICSE 2012 Software Engineering in Practice Track

Transcription

1 How Software Engineering Can Benefit from Traditional Industries Practical Experience Report ICSE 2012 Software Engineering in Practice Track Dr. Tom Sprenger CIO June 6, 2012

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3 Agenda Brief company presentation Industrial manufacturing Mapping of key elements Pillars of software industrialization Conclusions 3

4 AdNovum Swiss Engineering Quality Core Competence: High-End Security & Software Engineering Est privately owned joint-stock company Zurich (HQ), Bern, Budapest (Hungary), Singapore 275 employees, 70% graduate engineers 4

5 Customers and Industry Focus Finance Government Insurance EFD/BIT EVD/BLW EJPD/BFM UVEK/BAKOM Canton Zurich Tax Authorities Canton Zurich Building Management Logistics / Industry Telecom 5

6 History of Industrial Manufacturing Status of Software Engineering Image source: 6

7 Characteristics of Industrial Manufacturing Automation Mechanization / Technologization Division of Work Structuring / System Formation Standardization Interchangeability of Products/Parts Measuring and Control Primary Goals Continuous predictable production of goods with defined quality Continuous optimization of costs Broad consistency with Software Engineering requirements Idea: Develop software as you would process a product on an assemble line 7

8 Mapping of Manufacturing Key Elements Analogy: Car assembly line Industrial Manufacturing Software Engineering Manufacturing process Software engineering process Component supplier selection Technology management Supply chain management Dependency management Subassemblies / Components Software repository Assembly line with quality gates Automatic build & test Continuous controlling & information Quality & progress measuring system 8

9 Pillars of Software Industrialization 9

10 Software Engineering Process Process Models Waterfall, V-Model, RUP, Spiral, Iterative, Agile, etc. Formal Methods B-Method, Automated theorem proving, RAISE, VDM, etc. Process Key Elements Definition of phases Involved roles Tasks Deliverables Checkpoints / quality gates AdNovum Software Engineering Process Common-sense and widely established at least on paper 10

11 Technology Management Organisation on 3 Levels Strategic Tactical Operational Managed Process Driven by expert group Technology Investigation Purpose Efficient and controlled use of innovative technology Organize the technology landscape Knowledge Management Cost control License compliance (e.g. OSS licenses) 11

12 Technology Management Operational Example 12

13 Dependency Management Project Dependencies Fully qualified Declarative only Application Web Visualize dependencies Transitive dependencies analytics Purposes Know which technologies are in use Investigate critical project dependencies Reliably identify projects affected by e.g. a critical security issue in another component Gather information about software versions in use unused versions 13

14 Software Repositories Artifact Types Software components, Tools, etc. Established Standards Maven Repository, Nexus, etc. Key Requirements Nonambiguous name space Strongly managed Fully versioned Lifecycle meta information Purpose Provide software components from a managed single source Central place to company-wide approve or deprecate components/ component versions 14

15 Automatic Build & Test Preconditions Script-based execution (no user interaction required) Make consistent use of versioning Source code Third-party components Standardized project contract Defined set of and mandatory build targets (e.g. clear, init, build, dist, test) Self-contained project setup Challenge for Testing Define clear and reasonable quality and testing goals Provide test results in a structured manner Purpose Reproducible and predictable build and test results Low cost continuous execution 15

16 Quality & Progress Measuring System Goal Collect data for quality and progress indication Provide bases of decision-making for Operative decisions within project Optimization cycles Data Requirements Automatically collected on at regular intervals Structured Non-interpreted or rated Two main types Process centric data Product centric data 16

17 Quality & Progress Measuring System Process measuring: Optimize efficiency, improve results, minimize risks 17

18 Quality & Progress Measuring System Process measuring: Optimize efficiency, improve results, minimize risks 18

19 Quality & Progress Measuring System Process measuring example: Nightly Build 19

20 Quality & Progress Measuring System Process measuring example: Project dashboard 20

21 Quality & Progress Measuring System Process measuring example: Risk-Based Coverage Analysis (RBCA) 21

22 Quality & Progress Measuring System Product measuring: statistics, fault analysis, performance feedback Car with embedded diagnostics system CPUs with embedded analysis circuits 22

23 Quality & Progress Measuring System Product measuring: statistics, fault analysis, performance feedback In analogy to the "Analysis Circuits on a Chip we propose using special type of tracing as an "embedded measuring system" in software systems Advantages No additional tools are required to collect the data Measuring system is part of the software and therefore available from development to production Because the system is part of the software, application-specific context information can also be taken into account or measured System behavior can be tracked instantaneously, or it can be analyzed postmortem or offline 23

24 Quality & Progress Measuring System Product measuring example: end-to-end request tracing 24

25 Quality & Progress Measuring System Product measuring example: slow performance in 3 tier system Access 4 a.1 Presentation 4 EJB p e.1 fast 9 p.2 e.2 p.3 e.3 9 e.4 e.5 Methodname a.1 p.3 p.1 e.4 e.1 e.2... Cumulative Time 17 slow Number Method Cumulative of Calls Time [ms] Time [ms]

26 Conclusions How to Achieve Industrialization? Learn from the best and try to adopt Establish key building blocks and key concepts in your software engineering process derived from industrial manufacturing Establish measuring points to achieve structured output Set up continuous measuring environment Include measuring infrastructure into products/solutions Decide about improvement measures based on the output of the established measuring system Achievements at AdNovum Achieved a drastic improvement in predictability of results fault prevention overall engineering productivity 26

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28 AdNovum Informatik AG Dr. Tom Sprenger, CIO Röntgenstrasse 22, 8005 Zürich T