IEEE Computational Intelligence Magazine - May 2022 - 61

F. Category 6: EMT in Software and
Services Computing
Many problems in software engineering can
eventually be converted into optimization problem
instances. Examples include finding the
minimum number of test cases to cover the
branches of a program, or finding a set of
requirements that would minimize software
development cost while ensuring customer satisfaction. The
objective functions of such tasks generally lack a closed form,
hence creating a niche for black-box search methods like EAs-
underpinning the field of search-based software engineering [113].
What's more, as software services increasingly move to public
clouds that simultaneously cater to multiple distributed users
worldwide, a playing field uniquely suited to EMT emerges. A
schematic of EMT's potential in this regard is highlighted in
Fig. 9, where the scope of joint construction/evolution of two
distinct programs by the efficient transfer and reuse of common
building-blocks of code is depicted.
Concrete realizations of this idea for web service composition
(WSC) have been studied in the literature [114],
PDP1
1,800
1,750
1,700
1,650
1,600
1,550
2,300
2,200
2,100
2,000
1,900
1,800
0204060
Generation
PDP3
1,700
1,650
1,600
1,550
0204060
Generation
80 100
(b)
EEMTA
EA
FIGURE 8 Convergence trends (in routing cost minimization) of the representation learning-based EEMTA and a single-task EA on (a) {PDP1,
PDP2} and (b) {PDP3, PDP4}. Results are obtained from [112]. The shaded area spans 1 standard deviation on either side of the mean
performance.
2,200
2,100
2,000
1,900
1,800
1,700
0204060
Generation
80 100
80 100
(a)
PDP4
0204060
Generation
80 100
... as software services increasingly move to
public clouds that simultaneously cater to multiple
distributed users worldwide, a playing field uniquely
suited to EMT emerges.
[115]. The composition was achieved in [115] by formulating
the problem as one of permutation-based optimization,
where solutions encode the coupling of web services into
execution workflows. Given the occurrence of multiple
similar composition requests, a joint MTO formulation
was proposed. The experiments compared three permutation-based
variants of the MFEA against a state-of-the-art
single-task EA on popular WSC benchmarks. The results
showed that multitasking required significantly less execution
time than its single-task counterpart, while also
achieving competitive (and sometimes better) solution
quality in terms of quality of semantic matchmaking and
quality of service.
PDP2
MAY 2022 | IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE 61
Routing Cost
Routing Cost
Routing Cost
Routing Cost

IEEE Computational Intelligence Magazine - May 2022

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