AI for Software Engineering — Industry Landscape (03/Oct/2017)

AIFORSE Landscape Next Version: 18/Oct/2017
AIFORSE Landscape Latest Version:
12/Aug/2019.


“Artificial Intelligence (AI) for Software Engineering (SE)” is a new emerging Industry. It is dedicated to making Software Development better, cheaper and faster. Intriguing? Check the complete list of tasks (AIFORSE Community Program, “Goals” Section) the Industry is aimed to solve.

The Solutions (Companies/Products/Platforms/Researches) presented in the Landscape are divided into Categories by two criteria: (1) Software Development Lifecycle (SDLC) Phase and (2) Solution Readiness for the Market. Solutions inside Category are ordered alphabetically. Read more about these Categories below.

In the end of the Article, you will find a list of Solutions with References to their web pages.

If you have any comments and/or suggestions for Solutions, Categories or their mapping, please feel free to share them.


AI for SE Industry Landscape by AIFORSE Community

Columns Semantics

The Primary Criteria to categorize Solutions is the SDLC Phase. Independent on which Software Development Methodology you use, size of your team or type of your Product, you need to go through these Phases. We took the Software Engineering Body of Knowledge (SWEBOK) Knowledge Areas and merged some of them by few reasons. The main reason is that it is not always possible to unambiguously define which Solutions fall into which Category. Also, few of the SWEBOK Knowledge Areas were eliminated as not common and not related directly to SDLC.

Rows Semantics

Rows represent Maturity Level of the Solutions (highest row — most mature). The classification was made based on next criteria.

  • B2B Ready: there is a website for the Solution with at least one of the next information: Pricing, Customers, Testimonials.
  • B2C Ready: the same as “B2B Ready”, but AI is applied to SE indirectly: not through Tools for Software Engineers, but directly to Products, used by end Customers.
  • Academic Research: there is an extended description of the Solution in a Paper either in a Demo, but there are no known commercial applications.
  • Landing Page: there is only a web page with a description of a Solution, but with no information about Pricing, Customers or Testimonials.

Companies List (alphabetically)

Acellere | AppAchhi | Appdiff | Applitools |Codebeat |Codebots | Codota | DecibelInsight |Deckard AI |DeepCoder |DiffBlue |Fedr8 |Firedrop |Logz.io |Memorio.io |NARCIA |Near AI |Prodo.AI |Qualicen |RainforestQA |Re:infer |React VT |ReTest |RobustFill |RUBRIC |Sourcegraph |Stepsize |Talla |The Grid |UCDD |Uizard |Windmill |Wix |Zeenflow

Instead of Conclusion

You may have already counted that there are only 13 Solutions presented in the “B2B Ready” Category, which is the Core of the Industry. That’s not much, but there are other 13 Solutions in the “Landing Page” Category, and most of them were created in 2017.

One more challenge is related to that there are Solutions, which are created and used inside of Software Companies, but information about which is not available publicly. We would like to call such Companies to endorse the experience sharing to intensify the Industry development.

Forecast. Our forecast is that by the end of 2019 there will be 400 Solutions, falling into the ‘Ready for B2B’ Category.

AI for SE is new Machine Tools. Find out why in our next Article (follow the Publication to not miss it).


AIFORSE Landscape Next Version: 18/Oct/2017
AIFORSE Landscape Latest Version:
12/Aug/2019.