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The Profile of Software Changes in Reused vs. Non-Reused Industrial Software Systems Doctoral thesis presentation, An

The Profile of Software Changes in Reused vs. Non-Reused Industrial Software Systems Doctoral thesis presentation, Anita Gupta Trondheim, 28th May 2009. Overview. Introduction Company Background Research Design Results and Contributions Lessons Learned and Future Work. Introduction.

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The Profile of Software Changes in Reused vs. Non-Reused Industrial Software Systems Doctoral thesis presentation, An

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  1. TheProfile of Software Changes in Reused vs. Non-Reused Industrial Software Systems Doctoral thesis presentation, Anita Gupta Trondheim, 28th May 2009 Anita Gupta 28/05/2009

  2. Overview • Introduction • Company Background • Research Design • Results and Contributions • Lessons Learned and Future Work Anita Gupta 28/05/2009

  3. Introduction • Main focus: Investigate the relation between software changes and software reuse, and propose reuse guidelines based on these insights. • Trouble reports, change requests and changes in the code. • Research done in a large Norwegian oil and gas company, StatoilHydro ASA. • The SEVO project – Software EVOlution in Component-Based Software Engineering project (2004 to 2008) tries to understand software evolution, focusing on CBSE technology. Anita Gupta 28/05/2009

  4. Motivation • Software organizations (and researchers) have always been looking for effective strategies to develop quality software quicker and cheaper. • CBSE (Component-Based Software Engineering) is a potential technology to improve quality and time-to-market. • “the development of software by composing independent, deployable components” [Sommerville04]. • Our ability to develop and maintain such software is still inadequate. • Software changes is an important source of information for studying software reuse, evolution and maintenance. Anita Gupta 28/05/2009

  5. Research Goal • Investigate the advantages/disadvantages of systematic software reuse by analysing software change data (including both defect and non-defect changes). • Then, based on these insights, propose specific reuse guidelines (as an example of improvements) to StatoilHydro ASA, as well as general recommendations to software practitioners. Anita Gupta 28/05/2009

  6. Research Challenges • Indirect indicators of software quality, especially maintainability and reliability: • Defect density, CR density and change density not standard quality measures (RQ1). • Software reuse and its relation to software changes: • Few empirical studies have done convincing cause-effect analysis between software reuse and reduced defect and change density (RQ1). • Software evolution and maintenance: • Few studies have compared the change profile of a reused framework vs. software reusing it (RQ2). • Potential advantages/disadvantages of software reuse: • Challenges to reuse (and CBSE) are organizational, managerial and technological (RQ3). Anita Gupta 28/05/2009

  7. Research Questions • RQ1.What is the relation between software changes and software reuse, by comparing the reused framework vs. software reusing it? • RQ2.How do the reused framework and software reusing it evolve over time? • RQ3.What improvements can be made towards the actual reuse practice at StatoilHydro ASA? Anita Gupta 28/05/2009

  8. Software Reuse and Component • Software reuse: “is the systematic practice of developing software from a stock of building blocks..” [Morisio02]. • For instance, program libraries, COTS and OSS components, or entire software architectures. • A reused component in this study is a component that is reused in more than one product. • Two distinct activities: development for and with reuse. • Component: one of the parts that make up a software [emphasis added] system. May be a hardware/software and subdivided into other components [IEEE90]. Anita Gupta 28/05/2009

  9. Software Changes • Defect changes – Trouble Reports (TRs) • Results in several corrective changes • Non-defect changes – Change Requests (CRs) • Consists of perfective, adaptive and preventive changes • Changes in the code • Resulted from: • Defect Changes • Non-Defect Changes • Others Anita Gupta 28/05/2009

  10. Overview • Introduction • Company Background • Research Design • Results and Contributions • Lessons Learned and Future Work Anita Gupta 28/05/2009

  11. StatoilHydro ASA Background • Oil and gas company with 31000 employees. • Reuse strategy was initiated in 2003. • 100 developers in the IT department, 16 of them working with JEF, DCF and S&A. • Framework is called the “JEF framework” (20 KNSLOC). • JEF is reused in two applications “as-is”: • DCF, Digital Cargo Files (25 KNSLOC) • S&A, Shipment & Allocation (64 KNSLOC) • and in other projects • Data from three releases of JEF, DCF and S&A are analysed. Anita Gupta 28/05/2009

  12. Relation between JEF, DCF and S&A Anita Gupta 28/05/2009

  13. Characteristics of the systems • Seven components in JEF as a combination of COTS (Commercial-Off-the-Shelf), OSS (Open Source System) components, and in-house built code, initially only in-house built. • Development technology: Java, J2EE, and SPRING framework (OSS). • Software Configuration Management (SCM): Rational ClearQuest and Rational ClearCase tools. Anita Gupta 28/05/2009

  14. Overview • Introduction • Company Background • Research Design • Results and Contributions • Lessons Learned and Future Work Anita Gupta 28/05/2009

  15. Research Design • Quantitativestudies - exploring company databases (“data mining”) and assessing research questions/hypotheses. • Qualitative studies – textual web pages and documents and oral interview/discussions with developers. Combined with quantitative studies. • Three case studies and a small survey. • Rationale for mixed methodshas been: • Exploiting all available data, wider insight. • Triangulation of data/methods. Anita Gupta 28/05/2009

  16. Research Overview Phase 1 Phase 2 Phase 3 C1 Case study of change data related to the source code (quantitative/qualitative) 2008 C1 Case study of Change Requests (quantitative/qualitative) 2006-2007 P4 P2 C3 C3 P6 P3 Survey on developers’ views on software reuse (quantitative/qualitative) 2004-2005 C4 P1 C4 C2 Case study of Trouble Reports (quantitative/qualitative) 2006-2007 P3 C3 P5 C4 June 2008 August 2004 Results of study A lead to conducting study B Paper Anita Gupta 28/05/2009 Contribution

  17. Overview • Introduction • Company Background • Research Design • Results and Contributions • Lessons Learned and Future Work Anita Gupta 28/05/2009

  18. Results of RQ1 • RQ1: What is the relation between software changes and software reuse, by comparing the reused framework vs. software reusing it? • Systematic software reuse policy have helped to reduce the defect density of the reused software. • Interface-type defects higher for JEF than DCF and S&A. • Function-type defects higher for DCF and S&A: • Higher time-to-market pressure, unstable requirements and less quality control. • Cautious to involve changes into JEF. • The dominant change type is perfective changes, i.e. new/changed requirements and optimizations. Anita Gupta 28/05/2009

  19. Results of RQ2 • RQ2: How do the reused framework and software reusing it evolve over time? • Good initial design and stable requirements have reduced the change rate ofJEF. • Functionality and development practices affected maintenance mostly for JEF, DCF and S&A. Age and size affected it least. • Change profile for JEF and DCF were in line with the stage model proposed by [Bennett00], while S&A was different. • JEF went faster from the stage of extending capabilities to the stage where minor defect repairs are made than DCF. Anita Gupta 28/05/2009

  20. Results of RQ3 • RQ3: What improvements can be made towards the actual reuse practice at StatoilHydro ASA? • Late-coming developers did not know about the existence of a reuse training programme. • Shared information and experience repository would be beneficial for software reuse. • Analysis of CRs and TRs to improve current reuse process. • Updated software change reporting scheme, so that more correct and more complete information is reported: • Precise effort data • Component level information • Development phase information Anita Gupta 28/05/2009

  21. Systematic reuse • Lower defect densities of all types of defects, including: • assignment • checking • algorithm • data • timing • interface • relationship • GUI • function - Software maturity curve - Systematic reuse policy, e.g. to provide incentives to prevent and remove defect earlier in the life cycle - Systematic reuse policy, e.g. less changes performed on the reused components +/- The inherent properties (e.g. complexity, algorithm, size) of the reused software - Systematic reuse policy, e.g. reuse functionality is more likely to be well defined Lower defect density of the function-type defects - Systematic reuse policy, e.g. adoption of a domain specific library Back to slide 22 Back to slide 27 Anita Gupta 28/05/2009

  22. Summary of the Findings • Applications reusing JEF: • Faces more unstable requirements, longer time-to-market pressure, and less quality control. • The reused software, JEF: • Does not have a lower defect and change density than non-reused software. • Does not reduce the density of the most severe defects. • Should define and implement a systematic reuse policy. • We have proposed specific reuse guidelines to StatoilHydro ASA, and general recommendations to software practitioners. Anita Gupta 28/05/2009

  23. Overall Discussion of Results • Can we indicate that software developed for reuse is likely to be more stable vs. software developed with reuse? • We cannot! • The lower defect density, CR density and change density for JEF over its releases: • Software maturity curve, progressively in lower layers. • Software reuse policy. • The inherent properties (e.g. complexity, algorithm, size) of JEF; is a generic framework, and has less business logic than DCF and S&A. Figure Anita Gupta 28/05/2009

  24. Contributions, RQ and papers Anita Gupta 28/05/2009

  25. Contributions to SEVO project goals • G1. Better understanding of software evolution, focusing on CBSE technology. Better understanding of software maintenance and reuse benefits and challenges. Contributions C1, C2 and C3. • G2. Better methods to predict the risks, costs and profile of software evolution in CBSE.Improvements towards software reuse. Feedback given to StatoilHydro ASA. Contribution C4. • G3. Contributing to a national competence based around these themes, and G4. Disseminating and exchanging the knowledge gained.Results published at international/national conferences and workshops. Masters’ students involved. Contributions C1-C4. Anita Gupta 28/05/2009

  26. Contributions to StatoilHydro ASA • Upgrade defect and change reporting: To include effort data, and affected software components. • Improved configuration management: Rational ClearQuest and Rational ClearCase should be better integrated. • Improvements related to the O&S Masterplan (specific to StatoilHydro ASA): • Specific recommendations towards reuse, and at one place. • Define the terms: quality, time and cost. • The Masterplan should be more precise and to the point. • The organizational regulations should be less strict and more visible for the users in the company. Anita Gupta 28/05/2009

  27. Overview • Introduction • Company Background • Research Design • Results and Contributions • Lessons Learned and Future Work Anita Gupta 28/05/2009

  28. Lessons Learned (1) • Software reuse: Recommendations to Researchers • Diverse factors influence the relation between software reuse and (lower) defect density. Figure • Must consider functionalities and software development practices. • Defect and change request density correlate significantly with reliability [Li03], but does not represent causality. Anita Gupta 28/05/2009

  29. Lessons Learned (2) • Software reuse: Recommendations to StatoilHydro ASA practitioners • Improve their way of reporting software changes. • Careful quality control or testing of reused software to reduce the possible interface defects. • Staff who understand the reused software must be retained in the organization for a while after initial development of legacy code. Anita Gupta 28/05/2009

  30. Lessons Learned (3) • Software reuse: Recommendations to Software Practitioners in General • Define and implement a systematic reuse policy to reduce the defect density of reused software. • GQM feedback – improve precision of data collection in the short run. • Changes to the development process should be suggested in the long run. • Recording of available information and simple analysis. Anita Gupta 28/05/2009

  31. Future Work • Revising last paper (submitted to IST journal): Added complexity measures, and the new results indicate that JEF has a lower change density than both DCF and S&A. • Estimate software reliability by defect and change density. • Further studies on software evolution and maintenance. • Test processes for reused vs. non-reused software. • Effort distribution related to removing the causes of the most costly defects. • Amount of COTS or OSS used in the software projects, and integration problems. • StatoilHydro ASA’s reuse practices. • Aspects of software components that make them more or less fit for reuse. • Agile development methods vs. waterfall models. Anita Gupta 28/05/2009

  32. Acknowledgements • Thanks to SEVO (contract number 159916/V30), and NTNU for financial support. • Thanks to my supervisor, Prof. Reidar Conradi and colleagues at SEVO and IDI, Dr. Jingyue Li, Odd Petter Slyngstad and Dr. Daniela Cruzes. • Thanks to StatoilHydro ASA, Harald Rønneberg and Einar Landre, for the permission to perform studies and to publish the results. Anita Gupta 28/05/2009

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