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--- en:safeav:softsys:softtests [2025/06/05 12:09] – pczekalski
+++ en:safeav:softsys:softtests [2025/09/18 11:21] (current) – ToDo checked: raivo.sell
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 ====== Testing Software Systems ======
-{{:en:iot-open:czapka_b.png?50| Bachelors (1st level) classification icon }}
+{{:en:iot-open:czapka_m.png?50| Masters (2nd level) classification icon }}
-<todo @raivo.sell></todo>
+<todo @raivo.sell #raivo.sell:2025-09-18></todo>
+B. TRADITIONAL DECISION-BASED EXECUTION
+As cyber-physical systems evolved, information technology (IT) rapidly transformed the world. Electronics design trends revolutionized industries, starting with centralized computing led by firms like IBM and DEC. These technologies enhanced productivity for global business operations, significantly impacting finance, HR, and administrative functions, eliminating the need for extensive paperwork.
+----
+{{:en:safeav:as:picture3.jpg?400|}}
+Fig. 3. Electronics Megatrends.
+The next wave in economy shaping technologies consisted of edge computing devices (red in Figure 3) such as personal computers, cell phones, and tablets. With this capability, companies such as Apple, Amazon, Facebook, Google, and others could add enormous productivity to the advertising and distribution functions for global business. Suddenly, one could directly reach any customer anywhere in the world. This mega-trend has fundamentally disrupted markets such as education (online), retail (ecommerce), entertainment (streaming), commercial real estate (virtualization), health (telemedicine), and more. The next wave of electronics is the dynamic integration with physical assets, and thus even enabling autonomy.
+{{:en:safeav:as:picture4.jpg?400|}}
+Fig. 4. Progression of System Specification (HW, SW, AI).
+As shown in Figure 4, within electronics, there has been a progression of system function construction where the first stage was hardware or pseudo-hardware (FPGA, microcode).  The next stage involved the invention of a processor architecture upon which software could imprint system function.  Software was a design artifact written by humans in standard languages (C, Python, etc.).  The revolutionary aspect of the processor abstraction allowed a shift in function without the need to shift physical assets. However, one needed legions of programmers to build the software. Today, the big breakthrough with Artificial Intelligence (AI) is the ability to build software with the combination of underlying models, data, and metrics.
+In their basic form, IT systems were not safety critical, and the similar levels of legal liability have not attached to IT products. However, the size and growth of IT is such that problems in large volume consumer products can have catastrophic economic consequences [10]. Thus, the V&V function was very important.
+IT systems follow the same generic processes for V&V as outlined above, but with two significant differences around the execution paradigm and source of errors. First, unlike the PBE paradigm, the execution paradigm of IT follows a Decision Based Execution mode (DBE). That is, there are no natural constraints on the functional behavior of the underlying model, and no inherent properties of monotonicity. Thus, the whole massive ODD space must be explored which makes the job of generating tests and demonstrating coverage extremely difficult.  To counter this difficulty, a series of processes have been developed to build a more robust V&V structure. These include:
+)	Code Coverage: Here, the structural specification of the virtual model is used as a constraint to help drive the test generation process. This is done with software or hardware (RTL code).
+)	Structured Testing: A process of component, subsection, and integration testing has been developed to minimize propagation of errors.
+)	Design Reviews: Structured design reviews with specs and core are considered best practice.
+A good example of this process flow is the CMU Capability Maturity Model Integration (CMMI) [11] which defines a set of processes to deliver quality software.  Large parts of the CMMI architecture can be used for AI when AI is replacing existing SW components.
+Finally, testing in the DBE domain decomposes into the following philosophical categories: “Known knowns:” Bugs or issues that are identified and understood, “Known unknowns” Potential risks or issues that are anticipated but whose exact nature or cause is unclear, and “Unknown unknowns” Completely unanticipated issues that emerge without warning, often highlighting gaps in design, understanding, or testing.  The last category being the most problematic and most significant for DBE V&V.  Pseudo-random test generation has been a key technique used as a method to expose this category [12].
+In summary, the key underpinnings of the DBE paradigm from a V&V point of view are:
+)	Unconstrained and not well-behaved execution space for scenario test generation,
+)	Generally, less expensive simulation execution (no physical laws to simulate),
+)	V&V focused on logical errors not mechanical failure
+)	Generally, no defined regulatory process for safety critical applications. Most software is “best efforts,”
+)	“Unknown-unknowns” a key focus of validation.
+A key implication of the DBE space is that the idea from the PBE world of building a list of faults and building a safety argument for them is antithetical to the focus of DBE validation.

en/safeav/softsys/softtests.1749125357.txt.gz · Last modified: 2025/06/05 12:09 by pczekalski