The  Deliverable  8.1  describes  the  general  framework  to  be  further  used  in  D8.2  and  D8.3  for  the  socio-economic  impact  assessment  of  MIDAS  automated  SOA  testing  infrastructure.

In software engineering, a service-oriented architecture (SOA) is a set of principles and methodologies  for  designing  and  developing  software  in the  form  of  interoperable services.  These  services  have  well-defined  business  functionalities  that  are  built  as software components, which can be reused for different purposes.

Expected  success  from  the  implementation  of  a  SOA  is  usually  put  in  relation  to specific and measurable attributes, the so called quality attributes. When assessing the quality of a SOA, two main different points of view must be taken into consideration:
1) The SOA solution buyer (businesses, enterprises, firms) concept of quality
2) The SOA solution provider (and integrator) concept of quality With  reference  to  point  1),  SOA  quality  depends  on  the  SOAHspecific attributes/features for which SOA buyers, mainly enterprises and firms, hold a positive value.

More in detail, positive value is attributed by SOA buyers to all the SOA-specific features generating direct or indirect benefits to their activities/businesses. With reference to point 2), quality can be defined as the technical compliance of a SOA architecture with some predetermined standards.

Testing  can  be  considered  as  one  of  the  main  means  to  improve  SOA  quality,  both from a buyer and from a provider perspective, but, even though software testing has a long tradition and many tools have been developed to provide a good quality testing, on the contrary, SOA testing is quite a new domain, where some specific SOA features make testing activity very difficult to perform.

Despite  such  difficulties,  MIDAS  automated  testing  environment  will  dramatically improve the quality of testing: such a platform, in fact, would lead to not only better testing for existing architectures, but also to the testing of SOA that are not currently tested.

The main direct impact of MIDAS, therefore, will be, at first place, the production of higher quality level SOAs; as a corollary, higher quality SOAs will bring a positive impact on SOA solutions providers’ and buyers’ welfare.

An  appropriate  measure  of  such  impact  is  the  utility  differences  of  SOA  solution providers  and  SOA  solution  buyers  between  conditions  with  the  current  testing infrastructure/tools (base case) and conditions with the counterfactual infrastructure (in our case MIDAS). This can be expressed by summing over all SOA solution providers and buyers utilities as follows:

Δ economic welfare = ΣΔSOA provider utility +ΣΔSOA buyer utility.

More in detail:
a)  SOA providers utility will be positively affected because of:

  • higher profits due to both a mitigation of  the expenses for reengineering the produced SOAs after they are developed and released, and to a higher demand and market price.
  • better market reputation and higher (future) market share.

b)  SOA solutions buyers utility will be positively affected because of:

  •   higher profits due to a reduction in costs for buying and managing a higher quality SOA and to an increment in revenues generated by selling the product (good or service) the SOA user produces (the SOA, in fact, must be considered as an input, whose quality affects the quality H and, therefore, the price H and the quantity of the final product, hence affecting firms revenues);
  • higher market reputation, and higher (future) market share, due to the higher quality of the goods or services produced/offered by the firm.

In  addition  to  the  above  benefits  generated  on  MIDAS  direct  stakeholders  utility functions, more intangible and longHterm benefits will also be generated to the whole society, in terms of:

  •  incremental  network  effect  that  may  derive  to  firms  sharing  “inter-communicating” technologies;
  • incremental trust in technologies;
  • higher sustainability of the digital ecosystem.

Once  identified  the  main  fields  impacted  by  MIDAS,  the  approach  proposed  for measuring  such  impacts  is  based  on  the  SEQUOIA  methodology  for  socio-economic impact selfHassessment automation, adapted to the specific topic of SOA testing. More in detail, the proposed assessment process is articulated into 4 steps:

  1. Mapping the areas of impact
  2. Describing  the  situation  “without”  the  introduction  an  automated  SOA testing technology;
  3. Describe  the  counterfactual  situation,  “with”  the  introduction  of  an automated testing technology;
  4. Exercise final assessment analyses

The  final  assessment  report  will  be  done  through  a  multicriteria  and  multimensional description of all the considered impacts, by using the most suitable metric for each.

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